Come up with 3 stylometry research questions.

Aim for variety (Authorship Attribution, Diachronic Change, Genre/Register, Inter-author Similarity, Translation/Edition Effects, etc.

• Question: e.g., Do Charlotte vs. Emily Brontë differ in function-word use?

• Units/Scope: e.g., first 10 vs. last 10 chapters.

• Comparison: within-author / between-authors / across time / across genre / translation.

• Controls: balance length; originals only; match narrative voice.

Q1:

Explanations about your design:

Q2:

Explanations about your design:

Q3:

Explanations about your design:

Then review your question making process by reviewing the potential and limitations of stylometry.

i.e.,

• Stylometry CAN help because it uses unconscious function-word habits (MFW).

• Stylometry CANNOT answer themes, plot, sarcasm, historical meaning; beware topic-heavy confounds.

My Review:

Units/scope: about one famous novel of the author, and partition is each chapter of it.

Comparison: within author

Controls: because the length of each chapter might have an impact on function-words frequency, I will calculate density by dividing the number of function words by the number of pages in each chapter.

Q2. About one author who wrote both novel and essay, there is difference in style between his novel and essay?

Units/scope: whole of both

Comparison: within author, across genre

Controls: We should divide total number by total page because of the same reason in Q1.

Q3. Is translation and original version different? If different, it is because of difference in language or difference in writers?

Units/scope: original version of book, translation of it by some other writer, translation of it by translator

Comparison: translation -> between authors

Controls: compare equivalent parts

My review:

Q1- I learned that function-words habit of author is used unconsciously. Then, I think the density of function word should be nearly constant because it is not affected by author's conscious mind. So I want to prove it. But this has limitation because when author writes sentences, there exists sentence's style that some of them should use function word to indicate some other word earlier.

Q2- This might have limitation because novel and essay are different genre. Even if the result is 'different' we cannot know it means author's style is changed by genre or author's style is similar but the style of the specific genre is so different that author's particular style is not expressed.

Q3- I saw some translated book that it's original author and author who translated it are different. So I wonder author who translate books consider original version's text style when translating. So I will compare original vs. translation of it by translator first, and then compare translation of different authors. I think I may have limitations because translations might be made long time after the original books being made. Stylo cannot consider the difference in written era, so we cannot control variables perfectly.

Scope: Entire novels by authors who have both award-winning and non-award-winning works.

Comparison: Within-author (Comparing each author’s awarded books with their other published works.)

Controls:

-       Same author and format (not one novel and one essay)

-       Similar publication period

Q2: Do different awards favor different writing styles in particular?

Scope: Entire novels that have won or been shortlisted for different awards (such as Booker, NBA, Pulitzer).

Comparison: Between-awards (Comparing similarities and differences of books from different awards.)

Controls:

-       Same genre and format (such as mystery fiction)

-       Similar number of books per award

Q3: Do stylistic patterns of award-winning books influence the style of shortlisted works in the following years?

Scope: Award-winning novels from different years.

Comparison: Across time

Controls:

-       Same author, genre, and format

-       Similar publication period

My review

Q1: Stylometry can help because it might show some differences (like sentence length or complexity) that may appear when authors write and align with award trends. However, stylometry might not fully help because awards may be influenced by theme, cultural context, and politics, not only literary style. Also, function-word patterns may not reflect the writing’s quality directly.

Q2: Stylometry can help because it can show shared patterns and similarities in each award. Cluster analysis and PCA can also visualize which awards prefer specific writing styles. However, stylometry might not be able to answer because awards are also influenced by topics and jury opinions that are not reflected through language style.

Q3: Stylometry can help because it can show how literary style has changed and whether specific literary style become more or less common. However, stylometry might not help because writing styles are also influenced by social context and publishing trends, not just individual influence. Also, the criteria and preferences of award committees may change over time, making bias in the observed changes.

Units/scope: Famous short novels written by one author which have already been translated into other language(translated ones) and AI-translated ones (whole book)

Comparison: AI translated novels-human translated novels

Controls: Due to the AI's long-term memory is limited now, we should choose the short novel which has the length that AI can handle.

Q2. Does multilingual writers' works which is written in different languages shows similar pattern?

Units/scope: multilingual writers' works (whole book)

Comparison: Across languages

Controls: similar age, similar genre

Q3. How has the style of Haitian Creole literature evolved over time as it established its own literary standard independent from French? Can it be statistically demonstrated that the stylistic influence of French has decreased between early (mid-20th century) and modern works?

Units/Scope:

Early Corpus: Early novels and poetry written in Haitian Creole from the 1940s-1960s (e.g., Félix Morisseau-Leroy)(whole book).

Modern Corpus: Modern novels and poetry written in Haitian Creole from the 1990s-2010s (e.g., Frankétienne)(whole book).

Control Corpus: Works written in French by authors from the same periods.

Comparison : across time, within languages,

Controls : Genre Matching

Self-Review

1. Stylometry is maybe helpful for this analysis. By using its cluster analysis feature on a different works translated by various AIs, if the works form clusters based on the same AI model, we can statistically infer that a similarity exists among them. Conversely, if the results are mixed regardless of the model, it might suggest that the statistical pattern created by the AI model itself is weak.

   However, we cannot be entirely certain in the latter case. For example, if literary works of extremely different genres are translated and then analyzed, they are highly likely to form clusters based on genre. This emphasize the need to analyze the corpus while controlling for the statistical features inherent to the genre itself. Therefore, it is necessary to either conduct follow-up experiments based on the initial results or to flatten the statistical properties of genres by compiling a corpus that includes a wide variety of texts. This would require a large volume of text.

   It would be interesting if we can qualitatively interpret how differences in stylistic patterns emerge based on the AI model's training data (e.g., Claude Sonnet is specialized in coding, which menas it has learned from vast amounts of codes).

2. Stylometry is useful for this analysis. By appropriately selecting the MFW (Most Frequent Words), one can analyze the most-used words in works written in different languages. Alternatively, through PCA (Principal Components Analysis), it would be possible to properly analyze how a person's writing style changes depending on the language used when conveying similar content. The greatest difficulty of this research is the challenge of finding suitable books. There is a constraint that the author must have written on the same subject within a similar time period, ensuring their ideas have not significantly changed. This necessitates finding works by a renowned multilingual author, such as Yoko Tawada. This illustrates that in literary studies, unlike in the sciences where data can be freely generated through experiments for quantitative analysis, there is a heavy reliance on existing data. This can significantly limit the scope of research topics. I believe this is a limitation of stylometry when tackling this research subject, or more generally, when dealing with creative research topics.

3. Stylometry is useful for this analysis. By appropriately using MFW analysis, one can track the process of literary indigenization by observing whether the core vocabulary of Haitian Creole literature shifts over time from French loanwords to native terms or not. Furthermore, through PCA, it would be possible to demonstrate stylistic independence by visualizing how closely the early Creole corpus clusters with French literature, and conversely, how far the modern corpus has diverged to form its own distinct cluster.

   But it can not solve every problems by itself. It can be risky to attribute the cause of stylistic change solely to the process of 'decolonization.' It is difficult to rule out the possibility that other confounding variables such as shifts in global literary trends, the evolution of the genre itself, or simply an individual author's stylistic development. They may have influenced the results. The success of this research depends on controlling for these variables to isolate the specific effect of stylistic independence from French.

Units/Scope: Whole novels by each author

Comparison: Between authors

Controls: Equalize text length with excluding dialogue heavy sections

Q2. Does Jane Austen’s writing style change from her early novels (Sense and Sensibility) to her later works (Persuasion) in terms of average sentence complexity and use of personal pronouns?

Units/Scope: First and last novels by Austen

Comparison: Within author over time

Controls: Similar narrative voice, similar genre

Q3. Do first person and third person narrative sections in Emily Brontë’s Wuthering Heights show measurable stylistic differences in function word frequency and lexical diversity?

Units/Scope: Selected narrative sections within one novel

Comparison: Within author across narrative type

Controls: Equal length, consistent emotional tone or topic

My Review

Q1. Stylometry can help because it captures unconscious habits like function word patterns and sentence length, which is strong for authorship attribution. However, it cannot interpret tone, irony, or thematic choices. Moreover, genre differences could distort stylistic signals.

Q2. Stylometry can help because function word frequencies can reveal genuine stylistic evolution over time. However, it cannot explain why style is changed (e.g., maturity, editorial influence). Also, textual revision and historical spelling variation may confound results.

Q3. In narrative perspective differences, stylometry can quantify lexical/syntactic variation between narrative voices. Meanwhile, it cannot capture deeper narrative meaning or emotional perspective. Also, topic or character differences between narrators could bias results.

Scope

-      Texts in the same language with a political purpose

-      Texts that purpose is persuasion or argument

Comparison

-      Compare a single author’s political texts with the same author’s non-political texts to test whether the “political purpose” shows clear differences (to create a control case/group).

-      For the same issue (tax increase, immigration, education), compare texts through different authors/publications/parties.

Controls

-      Compare within the same genre and format.

-      Keep similar length.

-      Have to use texts written at a similar time.

-      Match the audience type (general public or experts & etc).

Q2: Do publications with different political leanings write differently about the same issue? (How do they differ?)

Scope

-      Political texts on multiple issues (election reform, immigration, economic policy, etc.)

Comparison

-      Compare between parties.

-      Compare between publications (or news).

-      Build controls by matching same political camp vs. different political camps.

Controls

-      Use texts written at a similar time.

-      Balance publications within each group.

-      Watch out for single-author bias (too many texts by one writer).

Q3: As elections go by, do parties’ writing styles converge or diverge?

Scope

-      Texts written across three or more consecutive elections.

Comparison

-      For each year, check the style distance between parties.

Controls

-      Compare texts written at a similar time.

-      Use text that written with same language.

-      Keep the same purpose (persuasion vs. information). Also run comparisons with different purposes to check consistency of analysis.

---------------------------------------------

Q1

I think the purpose of a text (persuading or arguing) leaves style marks(average sentence length, rates of periods/hyphens/colons, use of pronouns and demonstratives, and connector patterns) that are stronger than the changes that come from different authors.
→ So we can study the purpose effect by comparing a single author’s political texts with the same author’s non-political texts.

However, we cannot prove the features of politically motivated writing by looking only at style. If we also consider argument accuracy (for example, when an argumentative claim is false), the reliability of the analysis will drop. There is also a risk of over-generalization from a small sample.

Q2

If we match editorials or articles on the same issue, we can statistically compare parts of speech, sentence patterns, and period usage. To make the analysis more convincing, we should check differences between supporting parties, between publications, and by author.

But we do not know the hidden decisions made before readers see the text, so errors can appear. For example, we may not capture the publication’s editing direction, framing, the interpretation angle, or the logic structure well.
To Deal with this, I think that we should adjust for publication and audience effects. We should also include changes in each party’s stance on each issue in the analysis.

Q3

We can compute the stylistic distance between parties for each election year. We can draw a trend line on the yearly mean or median and judge whether styles converge (become more similar) or diverge (move apart). We can also zoom in on specific topics (economy, education, security, sports, etc.). By tracking the same party across years, we can see which party’s stance seems to change.

However, we cannot tell why stance or style changed. That needs methods other than stylometry. We should also consider whether there are year to year writing trends. If they exist, controlling them will give a better analysis.

- Scope:

Novels or short stories that each has received high and low critical evaluations. For example, literary award winners vs. poorly reviewed works on major review platforms.

- Comparison:

between-authors, within-author

- Controls:

Same genre

Similar publication period (within the same decade).

Comparable text length and narrative type.

Q2. Can stylometry identify a consistent authorial style across genres?

- Scope:

A group of authors who have written in multiple genres such as novels, essays, or journalism.

- Comparison:

Within-author, across genres

- Controls:

Same author and similar period of composition.

Balance text length across genres.

Q3. Can stylometry trace how collective literary style evolves over time?

- Scope:

Representative literary texts from different historical periods, such as early 20th century, mid-century, and contemporary works.

- Comparison:

Across time

- Controls:

Same language

Similar genre and form

Balanced number of works per decade and similar length

My Review :

Q1 - Stylometry can help predict it by finding whether there are measurable stylistic patterns that relate to how readers or critics determine the quality of an article. For example, one that perceived high-quality might have more complex sentences or richer vocabulary, while less successful works would show simpler and more repetitive language. These linguistic patterns could help explain why some writings area accepted more “literary” or sophisticated.

However, stylometry has clear limits here, because a “quality” is not something that we can measure or fully capture through numbers. A reputation often depends on cultural context or emotional impact. Function words or sentence length cannot fully explain the emotional depth of a story. So, while stylometry might find out some differences between praised and unpraised books, it is not able to tell us why people find a text meaningful or powerful.

Q2 - Stylometry can be a helpful way to see whether an author keeps its similar writing style even when they write different genres. People usually have certain habits in how they use small words or build sentences without acknowleding it. Because of that, unconscious habits might show up again in all of their works, regardless of the topic or form. For example, it would be interesting to check if a writer’s essays and novels still “feel” like the same person when we look at them through stylometric data.

However, stylometry doesn’t always fit perfectly when comparing across genres. This is because each genre has its own constraints that can change the way people write. For instance, newspaper article has a very different tone and structure from a novel or some personal essay. These rules contained in each genre can sometimes be mixed with the author’s natural writing style. So, while stylometry can reveal some consistency in an author’s writing, it might be hard to tell what actually comes from the writer and what comes from the genre itself.

Q3 - Stylometry can be used to trace how writing styles have changed over time by looking into features such as sentence length, vocabulary, or complexity. For instance, older literary works often tend to have longer and more formal sentences, while more recent writing styles might usually be shorter and more straightforward. Through this kind of analysis, we can obtain some picture of how general literary preferences and language use have changed across different periods.

However, stylometry alone cannot fully explain why these changes take place. Writing styles are surely affected by historical background, cultural values, and even publishing trends, which are factors that are far beyond what numbers can describe. Another issue is that if the dataset are confined in well-known authors, the results might not reflect the entire literary landscape. In short, stylometry can reveal patterns of stylistic evolution, but as to understand the real causes behind its patterns, it has to be supported by literary and historical interpretation.

In the 1700s century, marriage was a massive event which was a combination of each household. Of course, romance was one reason to marry, but this event had a deeper meaning. It was an opportunity for people to have a greater social level and money.

For authors who married in the middle of their writing career, I wondered if marriage influenced the words used.

Does the author’s use of quotation marks, punctuation, pronoun and auxiliary-verb ratios differ? Will sentence and paragraph structure shift after marriage?

• Units/Scope: Divide each author’s novels into two: ‘Published before marriage’ vs ‘Published after marriage’.  

• Comparison: 1) Within author, 2) Compare between each author

• Controls: Originals only, Compare the same amount of word (normal sampling, sample size: 5,000), Match the period written.

• Method:

-     (To find out the difference in a specific author only,) Compare words most frequently used with MFW(200), Culling(20%).

Using PCA and ‘oppose()’ - which helps visualize the main different words in each groups- can show which words were shifted in novels published after marriage.

-     (To check the common difference made,) Dialogue ratio, sentence length, punctuation ratios

Q1-1: Does Married vs. Never married influence the style of writing?

• Units/Scope: Choose more than 5 authors in each group: Married vs. Never married. Make sure the corpus sample of Married authors were published after their marriage. The sample of Never-married authors should be written after the average marriage age in the time.

• Comparison: Compare between two groups, Married vs. Never married.

• Controls: Originals only, Genre (Novels), Compare the same amount of word (normal sampling, sample size: 5,000), Match the period written.

• Method: Compare words most frequently used with MFW(200), Sentence length distribution, Paragraph length distribution, PCA plots for visualizing

Q2: Are there phrases or words frequently used by a specific gender in the late-18^th ~ mid-19^th century? Which methods were commonly used?

• Units/Scope: Gender of the author

• Comparison: Compare between two groups of authors; men and women.

• Controls: Originals only, Genre (Novels), Compare the same amount of word (normal sampling, sample size: 5,000), Match the period written.

• Method: Words most frequently used, The amount of quotes

Q3: Is my writing style similar with the books I’ve read in that period?

When I was young, I enjoyed reading English novels. I also had a hobby of writing in English. Will my writing style stick more to the books I have written?

• Units/Scope: Newbery awarded books, middle-grade fiction chapter books, other popular series (Bestsellers in 2014~19)

• Comparison: A text block from each book vs. My writing

Then highlight the books I have read in the period.

• Controls: Originals only, Genre (Novels), Compare the same amount of word (normal sampling, sample size: 1,000).

My Review:

Q1: Does the style of writing differ by the author’s individual life event? (Marriage)

This question and its additional question (Q1-1) is pointing to the narrative of each author. Stylometry doesn’t gather the history beneath the author, so the questions need additional research about the background narrative beneath the target authors.

However, stylometry can be used in this research since it’s crucial in figuring out the authors’ unconscious function-word habits (MFW), paragraph cadence, and sentence length distributions which close reading (maybe even the author) couldn’t detect.

Even if the output shows a notable change shifted in a novel, it’s hard to say the differences were made because of the marriage itself. There could’ve been other environmental, emotional changes individually.

Q2: Are there phrases or words frequently used by a specific gender in the late-18^th ~ mid-19^th century?

Scientific research can figure out when things were made by radioactive tracer. Can stylometry figure out when the novel was written? Also, can it figure out which gender wrote it?

The difference could be found by close reading, but using stylometry could give more specific details in data for answering this question.

Analyzing a large amount of data written in late-18th ~ mid-19th century, comparing words most frequently used between novels in the late-18th ~ mid-19th century to other times, it can point out the specific word use in the era.

Furthermore, this could help picture the atmosphere in the period.

Q3: Is my writing style similar with the books I’ve read in that period?

 This is a question I came up with after reading about stylometry.

Since it’s related to my own narrative, I already know what books influenced me, stylometry can help with the quantitative analysis. The question is looking for the similarities between my writing and the books I’ve read against popular books I haven’t read. Stylometry will be a good method to give a direct answer.

Additionally, for the narrative of the writer, I was also interested in emotional preferences. The author’s taste of reading such as which author complimented or hated who.

Although some disliked each other’s works, chances are there could be similarities in their writing. Even though one hated another because of the plot, the words used could’ve been a reference and vise versa. One can hate another for use of easy words but the plots could have been a motive.

This needed a deeper data of the author’s individual preference and history and gossip of the community of writers, so I couldn’t design it into a research analyzing with stylometry.

Units/Scope: Among the 2024-2025 posts, 100 reviews/reviews related to the release of the movie and 100 discussion threads (original poster body)

Comparison: within-subreddit, across genres of discourse (Review vs Discussion)

Controls: same period (Release timing effect control) / remove links, citations, tags / same length

Q2. Will comments that received a sign of persuasion ∆ (Delta) and failed comments in the discussion community r/ChangeMyView be stylistically distinct due to their functional language usage and argumentation structure?

Units/Scope: Among the 2024-2025 posts, 100 ∆ comments and 100 non-acquired comments

Comparison: within-subreddit, across outcomes (succeed vs fail)

Controls: same topic sampling / remove guide, link, citation block / same length

Q3. In historical community r/AskHistorians, are 'expert answers with flares' and 'non-flare general user answers' clearly distinguished in functional and conjunctive use?

Units/Scope: 100 flare answers and 100 non-flare top answers to questions on the same topic during 2024-2025 posts

Comparison: within-subreddit, between user roles (expert vs general user)

Controls: same topic sampling / remove footnotes, citations, and source notation /

Minimum length (1,000 characters or more) answer only

My review

Q1. Stylometry can capture the difference between unconscious functional word patterns and sentence length rhythms. It can visualize the difference in discourse structure between review and discussion types. However, it cannot deal with topic or mood, and topic differences by film genre or period can act as a disturbing variable. Therefore, care should be taken not to interpret "opinion character" only with stylometry. Also, we can categorize genre of movies and measure stylistic distance between each discourse and compare them. But, Since topics of movie(even if it’s just a movie) are changed along time. So, control sampling data of well-distributed date of posting is needed.

Q2. Stylometry can detect differences in the distribution of argumentative links (therefore, however, etc.), hedging expressions (might, perhaps), and sentence length depending on ∆. However, since non-logical factors (topic preference, author's reputation, etc.) also affect the success of persuasion, the interpretation of the results should limit the correlation around stylistic patterns. In other words, it is appropriate to focus on "what stylistic characteristics the successful comment showed" rather than "why persuasion succeeded". Since this question is affected by many factors, PCA analysis with error estimation with using R is desirable. PCA analysis is expected to tell us what’s most strong factor of persuasion in style (not in whole factor).

Q3. Stylometry can extract the difference between professional style signals (completed expressions may/night, connectors there/however, etc.) and average sentence length. We can perform culstering based on the extracted expressions. However, there is a risk that the complexity of the text or the difference in the amount of information in the text will be confused with the expertise itself. Interpreting the results should be 'linguistic consistency of expert groups' and be careful to consider them as content differences according to knowledge level.

• Experiment 1: Consistency of internal style of "Elements"

  • Units/Scope: The Body of each book (Book I, II, ..., XIII) of the "Elements"

  • Comparison: within author, within-work across books, Use rolling stylometry to determine if there are parts written by different authors in the "Elements”

  • Controls: Use the oldest edition of each book, include the proof process and formulas, classify the pictures drawn in the book separately

• Experiment 2. Comparison of the external style of all Euclid's writings with other ancient Greek works

  • Units/Scope: Include all books known for Euclid’s work(”Elements”, Catoptrics, Data, On Divisions, Optics, Phenomena) and other ancient Greek mathematical and scientific works (e.g. Aristotle's Organon, Archimedes's Measurement of a Circle, Apollonius of Perga’s Conics etc.)

  • Comparison: between-authors / across genre-matched works, Find the stylistic distance between each book using analyses like cluster analysis with Burrows’s Classic Delta Metric for Most Frequent Words

  • Controls: Use the oldest edition of each book, remove all formulas and mathematical symbols, paint only the colors of Euclid's works differently when visualizing

    
    

My Review: The first time I heard this question was a lecture called "Why is there no royal road to geometry?" by Lee, Eunsoo(이은수), a philosophy professor at Seoul National University. He suggested that Euclid might not be just one mathematician, but a group of mathematicians, which I thought was reasonable. This is because there was a very similar case in reality in modern times. A mathematician known by the name of “Nicolas Bourbaki” wrote a vast amount of mathematical books in the 20th century that contained the knowledge of the front lines in that time. These books were written from a set-theoretical/structural point of view and expanded logic through rigorous argument. This way of thinking had a great influence on modern mathematics. This is similar to the ”Elements”, which is called the world's first mathematical textbook, by introducing a method of proving propositions using only definitions, axioms, and postulates. But as it turned out later, Bourbaki was a pen name used by a group of French mathematicians, not individual. Furthermore, The practice of adding to the works of famous authors was not unusual in ancient Greek mathematics.[1] The Hippocratic Corpus, a collection of medical books containing Hippocrates’ teachings, is believed to contain a number of writings that Hippocrates did not write, and so is Pythagoras.

And what I want to note in Experient 1 is that equations and mathematical symbols can also play a important role in identifying the author. For example, the selection of mathematical symbols representing variables or geometric figures(like alpha, beta instead of a, b), choosing the representation and notation among identical ones, representing variables in ascending or descending order, and how much the detailed process to be written when expanding the formula, are directly related to the author's way of thinking and they are difficult to imitate. Additionally, since the details of the figures presented in the text vary widely from author to author, they can be collected separately to help identify authors using different analysis tools.

Therefore, Stylometry and other tools can provide a strong clues for whether "Elements" was written by a single author, Euclid, or if not, which part was written by another author. However, there are definite limitations. First, there are many versions of the “Elements" as it is very old, and there is a lot of controversy about which one is close to the original. Also, since the original one is written by ancient Greek, there will be a lot of difficulties in conducting stylometry. Sometimes, confusion can occur due to unknown words or grammar.

Q2. Can we distinguish pure freestyle and written freestyle only by looking at the lyrics?

• Units/Scope: The pure freestyle rap lyrics and the written freestyle rap lyrics of various rappers

• Comparison: across verses, Use supervised learning based on verses labeled by pure or written (training data) to obtain characteristics of each freestyle verse and function that distinguish the two

• Controls: Include filler words, implemente algorithms to determine rhymes

  
  

My Review: I love hip-hop music, and the comments in the rapper's freestyle rap video always have debate whether this freestyle is pure (pure improvised rap) or written (pre-memorized rap). I came up with this topic with this in mind. My guess is that when someone do pure freestyle, he or she has to keep thinking about the next lyrics while rapping, so the lyrics would be short, use repetitive words and filler words, and it's hard to create complex structures like multisyllabic rhymes.

Stylometry can be a good for identifying unconscious phrases, sentence structures, and frequently used words, especially in pure freestyles. However, the limitations are also clear. First, it is difficult to collect samples because there are few complete pure freestyles and the rapper doesn’t reveal it well. Second, with just the lyrics, it is difficult to know where the rapper emphasizes and what flow he or she uses for rap from lyrics alone. So there can also be rhymes that one can only notice by listening to the actual rap, but not with the lyrics alone. Third, it can be difficult to distinguish between the two freestyles using only the stylometry, as the unconscious clues will be greatly affected by external variables such as each rapper's habit, the type of beat and the BPM, and the situation of rapping.

Q3. Which style of Wikipedia article converges to as the number of contributors increases?

• Units/Scope: Body of each article in Wikipedia(English)

• Comparison: across articles, within article across time, Find the stylistic distance between each articles using analyses like cluster analysis with Burrows’s Classic Delta Metric for Most Frequent Words

• Controls: Extract text only, calculate the parameter (number of contributors)/(length of text) for each article, exclude articles generated by typo correction/reversal/article division, classify the subject of the article

  
  

My Review: When I enter Wikipedia while studying my major with textbook to search what I do not know, I sometimes feel a gap. Unlike major textbooks written by one author that clearly reveal one's own unique perspective of thinking, most of the notations, definitions, expressions, and explanations in Wikipedia are maintained standard and consistent among differnt articles. This phenomenon is especially well found in documents with many contributors. So, the hypothesis that the larger the (number of contributors to the article)/(the length of the article), the style of the article converges to some point came to my mind. And if there is such a convergent style, it will be closely related to LLM's style. LLM, as Ken Liu explained in his article, is based on the learning of many writings on the Internet. Therefore, it can be thought of as an object which has more contributors than any Wikipedia article, having ultimately converged style.

Thus stylometry allows us to see if each one’s unique "fingerprints" are diluted and integrated into one ultimate style. Specifically, Wikipedia articles, which are so extensive in quantity, can give us more reliable result. However, each Wikipedia article has a wide variety of contributors and each document would have its own biased contributors. For example, Wikipedia article about Korea would have more contributions by Koreans compared to other articles. And there are variables that depend heavily on the subject of the article regardless of the number of contributors. The description of the article about the Mona Lisa and the description of the article about Fundamentals of Calculus are unlikely to converge to the same point regardless of the number of contributors.

References

[1] Merzbach, Uta B.; Boyer, Carl B. (2011). "Chapter 5: Euclidean of Alexandria." A History of Mathematics (Third.). John Wiley & Sons. pp. 90–108. ISBN 978-0470525487

Q1: Do all the letters related to a case come from the same writer? -> To find who is/are the potential real killer(s)?

Units/Scope: Published letters about a case that officers approved

Comparison: within a case, across time

Controls: Original only, letter written in English only

Q2: Does the writing pattern of the potential real killer(s) get inspiration from any famous detective story writers? -> To guess the interest of the potential real killer(s).

Units/Scope: Published letters about a case that officers approved vs. 3 famous works from each 10 Famous writers during a specific time period

Comparison: within a case, between writers, within genre

Controls: Original only, letter written in English only, specific time period

Q3: Can stylometry observe or detect the pattern of a secret message in plain text? (e.g., if a letter was written with normal sentences, but the initial alphabet of each sentence could be arranged into a new secret sentence)

Units/Scope: 10 letters constructed in different patterns of writing, but every letter has the initial alphabet of each sentence arranged into the same sentence.

Comparison: between different writing patterns

Controls: English only, Balance length, the initial alphabet of each sentence in a letter is orderly arranged in the same sentence.

My review:

Q1: I think Stylometry could help in authorship attribution and diachronic change of each writer's pattern by lexical, syntactic, use of English (native/non native), and unconscious function-word habits. However, to find the potential real killer(s), there should be other supportive evidence from officers.

Q2: Stylometry might help in comparing writing patterns of all works, but there may be no relation between letters and famous authors’ works, which might be a waste of time. Nonetheless, this aspect of comparison could work with psychological or mental illness suspicion of letter writers and real patients.

Q3: It might be difficult for Stylometry to perform this function, but it could be developed to work with hint-finding/puzzling text. However, in a real situation, the secret messages from humans are way more complicated than we ourselves could imagine, so the Stylometry might take quite a long time to be developed to catch the complexity of people’s tricks.

• Units/Scope: novels which has a distinct change in emotions

• Comparison: within-author

• Controls: Since the style of sentences can be changed if the novel’s point of view is different, we should consider novels which has the same point of view.

Q2. When Western literature is translated into East Asian languages, how does the translator’s culture influence the length of sentences and the intensity of emotion expressions?

• Units/Scope: novels which translated the same Western novel into East Asian languages

• Comparison: between translators from Asia(e.g., China, Japan, Korea)

• Controls: Since there can be the difference between the language itself, we need to balance the length of sentences.

Q3. How does the style of sentences written by the same author be changed in different times?

• Units/Scope: several novels of one author, which has at least 5 years of time distance

• Comparison: within-author

• Controls: Since the style of sentences can be changed if the novel’s point of view is different, we should consider novels which has the same point of view.

Review

Q1. Stylometry can help because it can convert abstract concepts like emotional change into numerical features, such as length of the sentences. However, it could be confused because of the conversation, which has short sentences.

Q2. Stylometry provides comparable level of sentence length across different language structures, so this allows us to quantify the style difference between languages. However, it cannot consider the structure difference between different languages, so this might cause the fairness of sentence measures.

Q3. Stylometry can organize the author’s works chronologically and construct the model that can explain changes in styles of sentences. For example, it can explain the increase of sentence length or the change of function word by reflecting the author’s maturity. However, stylometry cannot consider the change of genre or topic, so this can make the error during the process of analyzing.

• Question : Does ‘style’ come from the form of the words or the real context?

• Units/Scope: Two corpora with clear genre contrast (e.g., SF novel and Poetry). Slice all texts into equal-length blocks (e.g., 5k–10k tokens).

• Comparison: Across Genre

• Controls: keep the same scenario/content across versions to separate form from context

• Explanations about your design

Do a comparision between two different genre. Then, pick one article and try to write it like the other(make a SF novel into a form of poetry)

Review : I guess that stylo cannot catch the context, and think of them as a poetry. Since it uses word-oriented calculation, it would more focus on the form of words instead of the full-context of the text. So the poetry-like rewrite will move on PCA and switch classification toward poetry even with topic(or the context is) fixed.

Q2: Is style reversible?

• Question: If you can measure the style, can GPT reversibly write a Austen-Like story?

• Units/Scope: Entire story of Austen and GPT.

• Comparison: Inter-author Similarity between Austen’s stories (that are not used for training) and the GPT-written stories.

• Controls: The stylo function that caculates and feedbacks the style of Austen(classify() to obtain per-class scores/decisions (Delta/k-NN/SVM) and record distance to Austen centroid, accuracy)

• Explanations about your design

Make a small GPT agent that writes a Austen-like story. Make GPT write it so it sounds like Austen. Then return the scores from stylo, and make it improve. Then, will the story gradually sound like Austen’s?


Review : From Stylo’s perspective, GPT outputs can register as Austen-like because the generator is being optimized toward stylometric signals that Stylo measures. However, how people actually feel remains uncertain. To evaluate this properly, we need a direct human study. A blinded authorship judgment with multiple raters to compare human perception would be valiable.

Q3: The1975 lyrics - which album is the most ‘British’?

Question : What album of the1975(which was my favorite band) most(or less) British? What makes the ‘British’?

• Units/Scope: Lyrics about the Entire/the title song of each album.

• Comparison: Diachronic change across albums and national register (UK vs US).

• Controls: For songs appearing on multiple releases, count them only in the earliest album to avoid duplication bias.

• Explanations about your design

Compare the 5 The-1975 albums and classify how ‘British’ each album is. Use UK vs US reference corpora and run clustering and classification; identify the album closest to ‘British’ literature and the one farthest away, and analyze why.

Review : Because the notion of “British” is ambiguous, this is closer to using Stylo as a tool for interpretation rather than configuring a single correct answer. A useful approach is to compare Stylo’s classifications with critics’ assessments of each album (and possibly listener surveys); alignment or divergence between the two can yield meaningful interpretations of stylistic “Britishness.”

• Unit/Scope: English novels written by authors from different fields. (literature majors vs. science majors) (ex. 5 authors from each backgrounds and two novels per author) Focus on linking words (categories: additive, contrastive, conclusive etc.)

• Comparison: Across-authors especially between two groups (literature vs. science/engineering writers)

• Controls: Match text length, Use original works, Standardize language to English, Same genre (to balance between emotional and logical narration)

• Explaination: Once, I read a novel written by an ecologist and later try to seek other works with similar tone. This led me to wonder ‘what kind of things are different in novels written by science majors?’ My hypothesis was that linking words would be differently used. (Science majors might rely more on conclusive words.) I think stylometry can help to solve this question. First, I will get the frequency of the linking words and classify into categories. Then, compare the frequency of emotional and logical linking words (conclusive & reason and result linking words as logical expression, contrastive and additive linking words as emotional expression) To control the parameter, I will strictly choose the genre because emotional and logical expressions are used more frequently in some genres.

• Review: Stylometry can quantitatively capture unconscious linguistic styles. Especially, it can find the frequency and distribution of function words such as linking words. (By MFW) Also, linking words can be easily classified into some categories. 

  However, it cannot interpret the hidden contextual meaning in the function word. Therefore, we cannot just match linking word with types of logical or emotional expression. Even though it contains contextually different meaning (Author use ‘however’ in the sentence, but that sentence shows the logical flow), stylometry cannot distinguish.

Q2. Does a Large Language Model (LLM) learn and reflect user’s writing style?

• Unit/Scope: Texts written by diverse users, Responses from LLM across different users. 

• Comparison: Within same LLM which interacted with multiple users.

• Controls: Balanced length, Control user’s prompt structure (standardized prompts templates but with their own writing styles), remove emoticons.

• Explanation: When I observe my friends’ LLM outputs, each LLM has different linguistic style. I was curious whether the LLM learns and reflect users’ writing style into its responses. I will use texts and prompts written by users as the base data for their own writing styles and compare with LLM's response. Then calculate Burrows's delta to get stylistic distance.

• Review: Stylometry can analyze stylistic similarity between texts using MFW, Burrow’s Delta and easily show the results by PCA. 

  In Stylometry, accurately characterizing an individual’s writing style requires sufficient amount of texts. However, in this case, users do not generate enough texts to reveal their own stylistic patterns. This can lead to significant errors for MFW. Also, this Stylometry cannot define authorial voice well in case of probabilistically generated language.

Q3. How the linguistic characteristics of Nobel Prize winning literature change over time?

• Units/Scope: Full texts of Nobel Prize winning literatures. (1901-2025)

• Comparison: Across-time from various authors

• Controls: Use original works, Perform sub-comparisons to control genre variation (novel, poetry, essay)

• Explanation: After Han Hang won the Nobel Prize, I became interested in this award. From that, I wondered how the features of works have changed over time. I assumed that highly acclaimed works might reflect social atmosphere or have writing style which was preferred in that era. I will get mapping data and PCA to compare the stylistic similarity through the era.

• Review: By calculating Burrows’s Delta, it is possible to quantitatively compare stylistic distance. Therefore, we can find certain styles are more favored in particular eras.

  However, stylometry has low resolution to analyze meaning and context. So it’s difficult to detect semantic similarity and cannot estimate historical significance and philosophical depth.

Units/Scope:

• Top 20-30 fictions sorted by Hits in AO3 (until we find 10 non-native written fictions)

• Assume fanfiction with a beginning note of "English is not my first language" or similar words (As attached) is written by non-native authors

• General Audience Ratings only

• M/M, NCT (Band) Fandom only

• Excluding OneShot fanfiction

Comparison: between-authors, across genre

Controls: Only the first chapter of that fiction is considered. This is because not every author finishes their stories.

Q2: What are the most important factors for readers to like a fanfiction? (i.e., pairings, style, theme, or language ability)

Units/Scope:

• Top 20 fictions sorted by Hits in AO3

• General Audience Ratings only

• K-pop Fandom only

• Considered all M/M, W/W, M/W

• Excluding OneShot fanfiction

Comparison: between-authors, across genre

Controls: Only the information written in the tags/settings and information in the first chapter.

Q3: Can Stylometry predict the style of one specific pairing of fiction (AxB and BxA)?

Units/Scope:

• Top 20 fictions sorted by Hits in AO3

• General Audience Ratings only

• One Specific pairing, i.e., AxB and BxA

• Considered all M/M, W/W, M/W

• Excluding OneShot fanfiction

Comparison: between-authors, across genre

Controls: Only the information written in the tags/settings and information in the first chapter.

Explanation: When actors known for playing superheroes appear in non-superhero films, audiences often still perceive them through the lens of their original superhero roles. Similarly, artists and fanfiction creators have a comparable relationship. Fans sometimes become attached to the artist's persona and write stories based on that. I would like to know if this observation is accurate. Additionally, can stylometry be used to analyze and identify the artist's style?

My Review:

Q1: We can count the distribution of native to non-native authors in the Top30. This can be easily analyzed by the number and rank. I truly believe that there might be some differences in the word choices of the non-native speakers, resulting in more friendly word choices. Stylometry might be able to analyze by comparing similarities and differences in word choices.

Q2: Stylometry might not be able to analyze everything we're curious about. However, Stylometry can help us analyze keywords like "love", "fight", or, more so, we can guess the trend of what people like.

Q3: Stylometry might be able to analyze and answer this. I truly believe there is a correlation between this.

Question: Can stylometry identify the same author when a polyglot writes literary works in different languages?
Units/Scope: Novels or essays written by bilingual or multilingual authors in two or more languages.
Comparison: Within-author, across languages.
Controls: Use original texts (not translations); balance text length and genre.

Q2. Stylistic Popularity (The ‘Money Code’ of Literature)

Question: Just as popular music often uses a “money code” that appeals to listeners, do best-selling literary works share common stylistic patterns that attract readers?
Units/Scope: Best-selling novels vs. critically acclaimed but less popular works.
Comparison: Across popularity levels.
Controls: Same language, similar genre and publication period.

Q3. Cognitive Style and Writing Patterns

Question: Can stylometry reveal patterns that reflect an author’s cognitive style or habitual thought processes?
Units/Scope: Essays or reflective writings by authors with known reasoning styles (e.g., analytical vs. intuitive).
Comparison: Across groups categorized by cognitive style.
Controls: Same language, genre, and text length; exclude quotations and dialogue.

My review:

A1. I don’t think stylometry would work very well for identifying the same author across languages. While stylometry can sometimes reveal unconscious stylistic traits that persist across languages, showing whether an author’s “stylistic fingerprint” transcends linguistic boundaries, most of the key features it relies on—like function words, sentence length, and punctuation patterns—change completely when an author writes in a different language. Higher-level features, such as narrative structure or character development, might feel distinctive, but they are difficult for stylometric methods to measure. Because of these challenges, using standard stylometry for cross-language authorship analysis seems very unlikely to succeed.

A2. Sentence rhythm, function-word balance, and pacing might be related to a book’s popular appeal. These features could make a text feel more readable, engaging, or catchy to readers. However, a book’s popularity is influenced by many other factors beyond style, including plot development, character appeal, marketing strategies, and cultural trends at the time of publication. For this reason, while stylometry might reveal some tendencies in best-selling works, it is unlikely to identify a definitive “money code” for literary success.

A3. Yes, I think stylometry can reveal patterns that reflect an author’s cognitive style or habitual thought processes in essays or reflective writings, where the author’s reasoning and argumentation are directly expressed. By analyzing most frequent words, function words, and syntactic structures, one can often detect tendencies such as analytical versus intuitive thinking, or even a generally positive or negative outlook. However, in literary works such as fiction or poetry, stylometric signals are often masked by narrative conventions, character voices, and stylistic experimentation, making it much less reliable for inferring cognitive patterns.

Q1: Do bilingual authors maintain the same style when writing in different languages? Also, is the style different from simply translating their work?

Units/Scope: Texts or conversations created by the same person in different languages, including interviews or written works, and translations of the work.

Comparison: Comparing a bilingual author’s style across different languages with their translated work.

Controls: The texts must be written by someone who is fluent in both languages.

Purpose/Explanation: Many people speak more than one language, and some authors have even written books or articles in more than one language. This makes me wonder whether an author’s unique style stays the same across languages. I was also curious whether writing directly in a second language feels different from translating their own work. Using stylometry could help analyze things like word choice, sentence structure, and punctuation patterns, but I wanted to see if this kind of analysis could work when the texts are in different languages and compare the results.

Q2: How much does an author’s style change over time and across cultural contexts? Can we tell if these changes are intentional, and is the author even aware of them?

Units/Scope: Texts or conversations written by the same person at different times. If possible, including interviews or explanations about the writing process would be better.

Comparison: Comparing the same author’s style over time and comparing this result with authors from different cultural backgrounds.

Controls: Texts must be written by the same person at different points in time.

Purpose/Explanation: People naturally change over time, and their writing style might reflect these changes. Authors may also change their style based on cultural influences or interactions with others. Studying these changes can show how writing styles evolve and can give insight into how cultural or social factors affect an author’s choices. It would also be interesting to explore whether the author is aware of these changes and which factors—such as government policies, censorship, or social trends—might influence the shifts in style.

Q3: Can analyzing speeches or statements by national leaders using stylometry reveal cultural characteristics or relationships between countries?

Units/Scope: Texts or statements from national leaders, such as speeches, public addresses, social media posts, or diplomatic communications.

Comparison: Comparing leaders from different countries, ideally around the same time to avoid historical context differences.

Controls: Communications should come from similar timeframes to reduce confounding factors.

Purpose/Explanation: Stylometry can help identify patterns in word choice, sentence structure, and their style in political communication. These patterns may reflect cultural norms, political values, or the relationships between countries. For example, some leaders may use direct language, while others are more formal or indirect. By comparing these features, researchers may show differences in communication style that relate to culture or the relationship between countries.

Review

Q1 Review: Stylometry allows researchers to measure patterns such as function word frequency, sentence length, and syntactic structure. However, since sentence structures and word meanings or nuances often differ across languages, it can be challenging to accurately distinguish an author’s style using stylometry alone. So, I think further research is needed to compare bilingual authors’ original works in different languages with their translations. Also, for this reason, I think the style of the bilingual authors’ work and the translation of the work would be different.

Q2 Review: Studies in stylometry have shown that it is possible to capture individual writing style, which varies among people. Therefore, I think that an author’s style may change over time in vocabulary, sentence complexity. By combining contextual information about the writing process, researchers can better distinguish between intentional stylistic changes and natural evolution. The writer’s interview or explanation would be strong evidence of the change, and this also shows how cultural background and social environment can influence writing style. Furthermore, it is possible that the author may be aware of and consciously notice these stylistic changes over time.

Q3 Review: In human communication, including political discourse, texts often carry cues about intention and relationships. Stylometry can identify these patterns, helping reveal cross-cultural trends and relationships between countries. This approach can also be applied beyond national leaders, for example, to ordinary conversations, to study social interactions. Analyzing such conversations with stylometry may offer a structured way to explore cultural differences and international relationships.

- Units & Scope: Transcripts from around 6–8 videos per channel 

-Comparison: Channel vs. Channel

-Controls: Use only official subtitles or cleaned transcripts. Intros, outros, and sponsor reads excluded to keep the tone consistent. Maybe aim for around 1,500–2,000 words per text sample? Only English-language videos of overlapping topics (e.g., space, evolution, climate). For fairness, upload dates can be kept within one year.

-Explanation + Review: I usually watch a lot of scientific YouTube videos and I feel like each channel has a sort of recognizable “tone”. Kurzgesagt feels collective and polished, Veritasium feels more personal and inquisitive, while CGP Grey feels kinda conversational but fast-paced. This question would test if those “voices” can be seen statistically through stylometry, such as differences in function-word frequency, pronoun use, or sentence length.

Stylometry can help uncover whether the “voice” we can sort of intuitively sense as viewers actually appears in measurable language habits. I’d expect Kurzgesagt to cluster apart because of its plural “we” narration and abstract phrasing, while Veritasium might show more direct address (“you”, “what if”, “let’s”). It would be interesting to see if those impressions I have are confirmed by data, or whether it is just a personal thing. However, stylometry can’t tell us about tone, visuals, or the emotional style of narration, which are all the features that make these channels memorable. It also can’t capture script editing or collaboration behind the scenes (many channels have multiple writers). So I would interpret the results as a hint of stylistic identity, maybe not a full picture of their “personality.”

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Q2: How does Jane Austen’s writing style shift between her narrative voice and her characters’ dialogue across her novels?

-Units & Scope: Keep it to three novels → Pride and Prejudice, Emma, Sense and Sensibility. For each, extract the narrative passages (outside quotes) and the dialogue scenes (inside quotes). 

-Comparison: Within-author (narration vs. dialogue), and across novels.

-Controls: Use only English originals. Match sample lengths, avoiding letters or prefaces, and same number of chapters or equal word count per section.

-Explanation + Review: This question would help to compare how Austen’s “storytelling voice” differs from her “conversation voice.” Her narration is famous for irony and precision, while her dialogue mimics polite 19th-century social interaction. Stylometry could reveal patterns like denser function-word use in narration (the, of, which) and more pronouns or contractions in dialogue (I, you, can’t).

I am always curious about how authors subtly switch styles without us noticing. Stylometry could help to quantify that stylistic shift and showing us how Austen’s language rhythm changes when she moves from observation to imitation of speech. I would expect her dialogue clusters to be slightly more “modern” (shorter, personal, spontaneous) than her narration but I can’t completely guarantee that hypothesis since I’ve only read one of the books. But stylometry would help to confirm or disprove that. Stylometry could show stylistic shifts, but it can’t explain why Austen switches voices. If she did it for irony, gender performance, or narrative distance. It also can’t read cultural context or emotion, which I believe are a major part of Austen’s wit. The results might show difference in word use, but interpreting that still requires close reading and historical understanding. Still, I think this could be a really nice complement to the close reading. I think I could use the obtained data patterns as clues to revisit her dialogue and see how they align with character voice and gender dynamics for the final project too. 

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Q3: Do fanfiction writers unconsciously imitate the original author’s style or do they develop a shared “fan community voice”?

-Units & Scope: Canon → excerpts from Harry Potter (≈10,000 words total).

Fan texts → 10 fanfiction stories (~1,000 words each maybe) from Archive of Our Own (AO3) 

-Comparison: Between-authors (original vs. fanfiction) and among fan-authors (within fandom).

-Controls: English texts only. It would be best to avoid parodies or scripts and focus on narrative prose for the fanfics. Similar length for all samples. Avoid crossovers or alternative universes. Same general tone (maybe adventure/drama-ish).

-Explanation + Review: Fanfiction exists somewhere in the boundary between imitation and innovation. Fans borrow the world of the author but ultimately write in their own style. Stylometry could show if their texts cluster closer to Rowling’s voice or if they cluster together instead. I am imagining the latter since there could be a shared community style which is shaped by online writing culture (shorter sentences, more direct dialogue, maybe heavier pronoun use).

This one feels especially fun to explore because it mixes creative communities with language data. I have not read Harry Potter before but I chose the book because of the example mentioned in class about JK Rowling’s hidden authorship being revealed through stylometry. Since she already has an established style, it would be fun to see how it compares to the fans of her book. Stylometry could highlight how collective writing habits evolve: do fans unconsciously echo Rowling’s function-word use, or have they built their own rhythm of expression after years of sharing online? I’d love to see whether AO3 fics written by different people still “sound” similar,  like a fandom dialect. What stylometry can’t show however, is intent or emotional resonance. It can’t capture the social and emotional motivations that are behind fan writing, whether it be humor, parody, intimacy, or shared community references. Online fandoms usually have their own slang and conventions. So, statistical differences may reflect internet language norms rather than imitation or originality. It also can’t tell if similarity comes from admiration, habit, or coincidence. 

Q1: Are dictionaries written in uniform styles? If not, what kinds of styles can we find in dictionaries?

Explanations about your design:

• Question: There are lots of different categories in the English language. If you look up Wiktionary, for example, you may find English adjectives, English interjections, English prepositions, English proverbs, English censored words, and so on. Comparing them, can we identify any meaningful cluster?

• Units/Scope: e.g. collections of some entries (e.g., a few collections of, say, a hundred adjectives and their meanings, plus a few collections of a hundred adverbs and their meanings) from a dictionary.

• Comparison: within-dictionary / across collections.

• Controls: balance length; remove redundant or unnecessary parts.

My Review: I've always thought that the writing styles of dictionaries are unlike anything. Dictionaries aren't mere lists of words and meanings, but writings. They have their own voices and styles. Learner's dictionaries feel kind, and online dictionaries feel more modern. Despite that, the apparent style within a dictionary is very uniform, even though they were written by many authors. However, this seemingly consistent style might not be as uniform as one might think. For example, function words usually have multiple meanings and are hard to describe, so their description tends to be distinct. Dictionaries sometimes provide detailed descriptions, but sometimes just synonyms, making their lengths shorter and increasing the frequencies of repeating words. Of course, the previous discussion is too simple to be meaningful, but what I'm trying to say is that there are some varieties of distinct styles within a dictionary. And it doesn't seem impossible to analyze it using cluster analysis or PCA. But it doesn't directly tell us the detail. It only tells us vague tendencies and correlations. So, it would still be difficult to get a meaningful conclusion even if we managed to find and analyze dictionary corpora.

Q2: How much can the writing style of a single author vary or be kept consistent? Do authors have control over their writing styles?

Explanations about your design:

• Question: For example, if we use stylometry to compare two writings of a writer that have a gap of 50 years, would they be identified as writings of a single author or writings of different authors? If the latter is the case, does it mean that the changes in their writing style are irresistible?

• Units/Scope: a collection of books written by an author (plus books by different authors if needed (for comparison)).

• Comparison: within-author / between-authors / across time.

• Controls: balance length; originals only. All the books used in this analysis must be written and published in the same period when the target author(s) was active. It may range up to 50 years, maybe.

My Review: I wondered if the writing style of an author can be controlled by being consciously aware of it. When I once read a story that I wrote in my childhood, it felt as if it is written by a different person. It is inevitable, though I wasn't conscious about my writing style at that time. However, there are some prolific writers who write the same book series for many decades. Probably they succeeded in maintaining their writing styles. But what about their non-series books? Are they also in the same style? For these reasons, I think one of the best target authors for our purpose is an author who wrote a long book series and who also wrote many other books, like Stephen King (but it might cause some bias). Cluster analysis, bootstrap consensus tree, and other methods can be used to compare and classify these books. But I'm not sure if a single author's style can vary that much. In that case, we might reach an inaccurate conclusion. Yet another option is to compare with different authors. Then we may expect a better result. Stylometry might be able to tell how much one book varies from another via comparative methods, but stylometry doesn't explain how they differ, so we should not attribute too much meaning to it.

Q3: Can stylometry differentiate professional, amateur, and non-native writings?

Explanations about your design:

• Question: Do native writers have something special compared to the non-natives? Do professional writers have something special compared to the amateurs? If so, can stylometry detect them?

• Units/Scope: a collection of texts written by professionals, amateurs, and non-natives.

• Comparison: between-author.

• Controls: balance length; all the texts in the collection should have a unified context and theme (e.g. writings for a contest).

My Review: The question itself is, I think, way more straightforward than the other two. But it isn't really as easy as it first seems. Probably they can be differentiated using stylometry, but I don't think there are universal writing styles that represent professional, amateur, or non-native writings. These three terms simplify the variety of styles too much. There must be lots of sub-branches within each term, and a professional writing may resemble an amateur writing more than another professional writing. So, these three terms might not be the primary branches into which the whole collection of writings is subdivided.

Question: Do significant stylistic differences exist between the podcast hosts A and B regarding the frequency of personal pronouns and definite articles in their economic news scripts?

Units/Scope: Collect and use the scripts from 10 weekly briefing episodes from each host's podcast. Balance the corpus by slicing each script into contiguous, equal-length samples of 8,000 words each.

Comparison: Between-Authors and Host Style Comparison (Inter-channel Style).

Controls: Match the topic (all scripts must cover 'weekly economic trends'), and set similar audience profiles (e.g., expert vs. general public) to control for register variation.

Explanations about your design: This question applies the core principle of stylometry: authorship attribution based on unconscious function-word habits. Pronouns (like 'I' and 'we') and definite articles are powerful function words that reflect the host's implied authority or desired level of intimacy with the listener. By measuring the frequency of these subtle features, the analysis can quantitatively distinguish between the unique stylistic fingerprint of the two hosts, even when discussing the same subject matter.

Q2: Diachronic Change (Blogger's Style Evolution)

Question: Has there been a significant diachronic change in the average sentence length and syntactic complexity between a tech blogger D's early blog posts (Year 1) and their recent professional newsletters (Year 5)?

Units/Scope: Collect 20 early blog posts and 20 recent newsletter articles. Use the rolling.delta() or rolling.classify() technique to analyze the shifts in style across the author’s career output.

Comparison: Within-Author over time (Diachronic Change).

Controls: Match the core content genre (all texts must be 'tech reviews'). Assume the shift in formality (casual blog vs. professional newsletter) as the variable under investigation rather than a confound. Exclude specific technical jargon (proper nouns) to minimize topic interference.

Explanations about your design: This research measures the evolution of a creator's writing style, driven by professional maturation or a shift in medium (register). Sentence length and punctuation are crucial structural features for measuring complexity and rhythm. The rolling analysis technique allows the study to trace when the stylistic differences became statistically significant, enabling a critical discussion of whether the observed change aligns with the author's career advancement or adaptation to a new professional format.

Q3: Register Comparison (Social Media vs. Long Form)

Question: Does a clear register difference exist between long-form online magazine columns and short-form Twitter (X) posts written by the same entertainment critic E, as evidenced by the frequency of contractions and emphatic interjections?

Units/Scope: Set up two distinct corpora: 100 Twitter posts (using full text) and 10 magazine columns (using 500-word samples from each). Use the oppose() function to extract the most distinguishing features between the two media formats.

Comparison: Across Genre/Register (Media Form Comparison).

Controls: Identical Author (Critic E is the sole speaker) and Topic Match (all content relates to 'film or media critique'). Treat the inherent stylistic differences (e.g., mandated brevity in tweets) as the primary object of comparison.

Explanations about your design: This question analyzes how medium constraints force a writer to adapt their style, known as register variation. Contractions (e.g., "don't," "it's") and interjections (e.g., "Wow!") are strong stylistic markers of informality and immediacy. The oppose() function is ideal here, as it quantifies which of these markers are preferred in the high-speed, informal Twitter corpus versus the avoided in the formal, long-form column corpus, providing a clear statistical measure of the stylistic gap between the two registers.

My Review: Stylometry's Potential and Limitations

Stylometry CAN help because all three questions focus on unconscious, quantifiable linguistic features—specifically function words, structural complexity, and punctuation/exclamatory markers. These elements form the creator's unique stylistic fingerprint and are reliably measured by MFW analysis and multivariate methods (PCA, Delta). Applying these methods to non-traditional digital texts (podcasts, social media) effectively broadens the scope of authorship attribution and register analysis.

Stylometry CANNOT answer questions about the content's quality, subjective emotional resonance, or thematic intent (e.g., is one article "funnier" or "more insightful"?). Crucially, we must beware of topic-heavy confounds (highly specialized vocabulary unique to one topic), which must be controlled for through careful feature selection and corpus balancing to ensure we are measuring style, not just subject matter.

Novels of different lengths written by an author.

Within-author.

Controlling author.

2.    Are there any common grounds among books which are easy to read?

Books that are easy to read and books that are difficult to read.

Controlling the topic of genre of the books.

Between-author

3.    How interaction between authors affects their writing style?

Books from two authors who have interacted with each other for long time.

Choose books from various periods of their lives.

Between-author, across time.

Controlling the type of books. (ex. Novel)

Review

1.    An author may change one’s writing style depending on the length of the book. Length of sentences and frequency of words may be changed. So stylometry can help.

2.    We have to distinguish books that are easy to read and difficult to read. This work cannot be helped by stylometry. If the distinction has made, we can use stylometry to figure out whether there is distance between dose groups. However, difficulty in reading may affected by the contents of the book as well, so stylometry may be not efficient.

3.    Stylometry will help because we want to figure out how interaction between authors affects their unconscious usage of words.