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      <title>Red Team  by Aoife Byrne</title>
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      <pubDate>2016-10-07 15:17:19 UTC</pubDate>
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         <pubDate>2016-10-07 18:20:13 UTC</pubDate>
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         <pubDate>2016-10-07 18:24:57 UTC</pubDate>
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         <author>c16497664</author>
         <link>https://padlet.com/c16497664/3tvq6tfqfn4u/wish/136122693</link>
         <description><![CDATA[<div>Content Analysis Options: Which one?&nbsp; <a href="https://www.youtube.com/user/caseyneistat">Casey Neistat</a> vs <a href="https://www.youtube.com/user/vlogbrothers">vlog brothers</a> vs <a href="https://www.youtube.com/user/sxephil">Philip Defranco</a><br><br></div>]]></description>
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         <pubDate>2016-11-08 15:30:04 UTC</pubDate>
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         <title></title>
         <author>valerie_connor1</author>
         <link>https://padlet.com/c16497664/3tvq6tfqfn4u/wish/136135985</link>
         <description><![CDATA[<div>Paul Gaffney - Series in Gallery of Photography. Perigee</div>]]></description>
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         <pubDate>2016-11-08 16:02:48 UTC</pubDate>
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         <link>https://padlet.com/c16497664/3tvq6tfqfn4u/wish/136561483</link>
         <description><![CDATA[<div>For this presentation are group have read chapter 4 and cheaper 5 of Gillian Rose's book Visual Methodologies we will be attempting to give a summery of these two chapters and give are own insites while also seeing how we can relate chapter 4 "The good eye: Looking at pictures using compositional interpretation" with vlogs and the vlog brothers and comparing chapter 5 "Content analysis and cultural analytics; Finding patterns in what you see" with the work shown at the moment in the gallery of photography  Paul Gaffmeys work "Perigee"</div>]]></description>
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         <pubDate>2016-11-09 20:14:06 UTC</pubDate>
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         <link>https://padlet.com/c16497664/3tvq6tfqfn4u/wish/136571310</link>
         <description><![CDATA[<div>Content analysis was originally made as a way of analysing journalism in mass media. It is a way of dealing manually with large numbers of images. The way we did this was we looked at a number of images in class from national geographic based on Ireland and came up with key words or code words that came up in number of pictures as a way of sorting images. These code words had to be specific to the pictures and come up threwout  the images (counting the frequency of these visual elements.)</div>]]></description>
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         <pubDate>2016-11-09 20:49:33 UTC</pubDate>
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         <author>c16497664</author>
         <link>https://padlet.com/c16497664/3tvq6tfqfn4u/wish/136649591</link>
         <description><![CDATA[<div>What we should look at October 2007 vs October 2016 </div><div>That's nine years difference </div><div><br></div><div>What we can find out, is there a difference in content between October 2007 and October 2016? </div><div><br></div><div>Code I suggest </div><div><br></div><div>Is nerd fighter art work shown </div><div><br></div><div>Is project for awesome talked about </div><div><br></div><div>Does either brother get new glasses or  a hair cut </div><div><br></div><div>Hank sings/ plays an instrument </div><div><br></div><div>John talks about a book and shows cover </div><div><br></div><div>Are they outside there house <br><br></div><div>Video quality changes </div><div><br></div><div>Montage is shown<br><br>Puff levels are high</div><div><br></div><div>Baby's are mentioned <br><br>Guests in vlog</div><div><br></div><div>Eoghan feel free to add more when you watch some :3 </div><div> </div><div>Go red team </div><div><br></div>]]></description>
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         <pubDate>2016-11-10 08:44:57 UTC</pubDate>
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         <link>https://padlet.com/c16497664/3tvq6tfqfn4u/wish/136887673</link>
         <description><![CDATA[<div>Content Analysis Ch. 5<br>In addition to coding the National Geographic articles we also went to the Sven Augustijnen exhibition where we used a number of codes, or key words, to analyse the images on display. Examples of these codes used were: Advertisements with alcohol - 11, Funerals - 9, Portraits of politicians - 30<br>These codes help to condense an amalgamation of images into labels that can be quantified. The codes must be exhaustive, exclusive and enlightening. They must be distinctly defined so that if anyone else were to use these codes their results would&nbsp; be the same.&nbsp;<br>Strengths of Content Analysis:<br>-By using it as a method it helps to break down a mass of images that are being examined into an achievable amount.<br>-It is unbiased as the analyser has to be objective when looking at the images.&nbsp;<br>-It is methodological and so can be done quickly.<br>Weaknesses:<br>-There is only a focus on the content of the images; the production of it and the target audience are not investigated.<br>-Cultural significance is not considered.<br>-Thus the results it can achieve are limited.<br><br>-Grace</div>]]></description>
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         <pubDate>2016-11-10 20:35:05 UTC</pubDate>
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         <title></title>
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         <link>https://padlet.com/c16497664/3tvq6tfqfn4u/wish/136898293</link>
         <description><![CDATA[<div>Cultural Analytics Ch5<br>In using this method images must be in a digital format. Often the analyser uses an algorithm whereby the computer automatically searches for the information required. This saves time as sampling is not needed and the images do not need to be examined manually.&nbsp;<br>The resulting images will often be arranged ina collage; each image a small thumbnail version. This helps the analyser quickly view the overall product or result.&nbsp;<br>Strengths:&nbsp;<br>-Time effective<br>-Can interpret the cultural significance of images, to a certain extent.<br>-Unequivocally objective as it is a software doing the analysing.&nbsp;<br>Weaknesses:<br>-Not as effective as Content Analysis as can only analyse concrete labels such as colour or composition; it cannot&nbsp; analyse something subjective or that needs more data such as fashion images.<br>-The results needs additional medium of information or explanation ie. writing.&nbsp;<br>&nbsp;-Grace</div>]]></description>
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         <pubDate>2016-11-10 21:26:20 UTC</pubDate>
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         <title></title>
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         <link>https://padlet.com/c16497664/3tvq6tfqfn4u/wish/137131969</link>
         <description><![CDATA[<div>Finding your images.<br>This part of the chapter looks into why? And where? To find your images for content analysis. ( e.g Lutz and Collins National Geographic.) chosen due to its high rating in the USA and having 37 million readers worldwide. The images. Chosen must relate to the question being asked. You also must then come up with a way of picking images out weather it be random, stratified, systematic, or clusters. <br><br><br></div>]]></description>
         <enclosure url="" />
         <pubDate>2016-11-12 13:41:55 UTC</pubDate>
         <guid>https://padlet.com/c16497664/3tvq6tfqfn4u/wish/137131969</guid>
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         <title></title>
         <author></author>
         <link>https://padlet.com/c16497664/3tvq6tfqfn4u/wish/137132429</link>
         <description><![CDATA[<div>Devising your categories for coding.<br><br>This section is all about how you choose your codes? And how your codes relate to the images? The coding categories must be exhaustive, exclusive, and be enlightening. It is the process of reducing material in photographs into codes. Looking for something interesting, unusual or unexpected to gather further analysis of images. Lutz and Collins use 22 different codes in there work on the national geographic all of which are exhaustive and exclusive. </div>]]></description>
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         <pubDate>2016-11-12 13:53:21 UTC</pubDate>
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         <title></title>
         <author>ogin_</author>
         <link>https://padlet.com/c16497664/3tvq6tfqfn4u/wish/137184092</link>
         <description><![CDATA[<div>Chapter 5 discusses two methods for analysing large number of images, first method we will discus is content analysis:<br>Content analysis has a number of rules need need to be followed when analysing images or text for the end information to be completely reliable </div>]]></description>
         <enclosure url="" />
         <pubDate>2016-11-13 12:00:12 UTC</pubDate>
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         <link>https://padlet.com/c16497664/3tvq6tfqfn4u/wish/137194841</link>
         <description><![CDATA[<div>Paul Gaffney – Perigee exhibition : The Gallery of Photography</div><div><br></div><div><strong>Technologies and the Production of the Image</strong></div><div><br></div><div>Paul Gaffney put together this exhibition to investigate the different ways of experiencing and representing the landscape. In this exhibition there are two bodies of work. One called Perigee, which refers to the point in the moons orbit where it is closest to Earth. In preparation for the final images Gaffney walked through the forest during the day, taking black and white Polaroid photographs of routes he found evocative. He went back at night following the same routes and photographed them using only the light of the moon.&nbsp;</div><div><br></div><div>The other body of work entitled Stray entails a series of photographs taken in a dense pine forest with very little light. These were displayed using multiple slide projectors that were constantly changing. This, Gaffney said, was to give one the feeling of being at the edge of their comfort zone and moving through a disorientating environment.&nbsp;<br><br></div><div><strong>Compositional Interpretation</strong></div><ul><li>Content</li><li>Gaffney’s photographs come under the genre of landscape photography. They simultaneously convey the sereneness of being out in nature away from the things of man, while also evoking a sense of uncertainty, feeling of being lost. The images themselves show close ups of branches and trees. Often those in the foreground are blurred, encouraging the viewer to look deeper into the photographs. There is a single spotlight shining down on each image. This highlights the white tones in the photographs, bringing the branches almost closer to the foreground. Additionally the use of spotlights gives the images an almost three dimensional effect.&nbsp;</li><li>There are no titles or descriptions on each photograph, leaving any interpretations up to the viewer.&nbsp;</li><li>&nbsp;</li><li>Colour</li><li>The hues that dominate in Gaffney’s photographs are black, brown, green and white. The consistency of these colours help to bring these images together as a collection whilst also highlighting the differences between them.&nbsp; The value of these images is low. This is because the background in all the images is black. This gives the images a sense of depth.&nbsp;</li><li>&nbsp;</li><li>Spatial Organisation</li><li>Due to the lack of light in Gaffney’s images and the dark background it is difficult for the viewer to gauge whereabouts the photograph was taken from. It could have been taken from ground level or from up high in the trees, as there is no sky or ground seen to give perspective. This uncertainty further adds to Gaffney’s intentions of evoking feeling of “a mysterious, psychological wilderness”. The viewer is immersed in the environment. Some of the images are framed by the branches of the trees. This creates a vanishing point and encourages the viewer to look deeper into the image.&nbsp;</li><li>&nbsp;</li><li>Light&nbsp;</li><li>Moonlight was the sole source of light in Gaffney’s images. This creates an evocative mood, one reminiscent of our past where only natural light was available. It gives an almost romantic atmosphere to the photographs.&nbsp;<br><br></li></ul><div><br></div><div>&nbsp;&nbsp;&nbsp; -Grace</div>]]></description>
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         <pubDate>2016-11-13 15:14:40 UTC</pubDate>
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         <title></title>
         <author>ogin_</author>
         <link>https://padlet.com/c16497664/3tvq6tfqfn4u/wish/137415298</link>
         <description><![CDATA[<div>I coded two sets of ten videos of the Vlog Brothers using the same codes for each set, one set were made in 2007 and the the other were made in 2016. I done this so we could see how much has changed or if anything has.<br><br>2007.<br><br>Is nerd fighter art work shown?: 1<br><br>Is project for awesome talked about?: 0<br><br>Does either brother get new glasses or a hair cut?: 2<br><br>Hank sings/plays instrument: 0<br><br>You can see a book in the video: 3<br><br>Are they outside?: 5<br><br>Are they inside?: 8<br><br>Are props used?: 6<br><br>You can only see their head on the screen: 7<br><br>2016.<br><br>Is nerd fighter art work shown?: 6<br><br>Is project for awesome talked about?: 2<br><br>Does either brother get new glasses or a hair cut?: 5<br><br>Hank sings/plays instrument: 2<br><br>You can see a book in the video: 5<br><br>Are they outside?: 1<br><br>Are they inside?: 9<br><br>Are props used?: 5<br><br>You can only see their head on the screen: 6<br><br><br></div>]]></description>
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         <pubDate>2016-11-14 15:52:00 UTC</pubDate>
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         <title></title>
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         <link>https://padlet.com/c16497664/3tvq6tfqfn4u/wish/137467704</link>
         <description><![CDATA[<div>This section goes into how to code a set of images. The coding categories that you use for a set of images must be clear and only have one set of interpretation. ( This makes the coding replicable. ) <br>Ross</div>]]></description>
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         <pubDate>2016-11-14 17:39:32 UTC</pubDate>
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         <link>https://padlet.com/c16497664/3tvq6tfqfn4u/wish/137498962</link>
         <description><![CDATA[<div><br></div><div><br></div><div>Gillian Rose says  „ This is a term I have invented for describing an approach to imagery that has developed through certain kinds of art history, and essentially in relation to painting in the Western tradition of fine art.” </div><div><br></div><div>„The Good Eye” refers to paying attention to every detail in an image . This method involves focusing on different factors that make up an image and treating those as hints in the final interpretation of the image.</div><div>The factors include:</div><div>Composition: One of the most important element of the image to be examined using this method.</div><div>After that there are The other factors .                                                     -Content </div><div>-Colour     Hue, Saturation, Value</div><div>-Spatial Organisation</div><div>-Screen ratio</div><div>-Screen frame</div><div>-Screen plates</div><div>-Multiple images superiompositions</div><div>-Shot distance</div><div>-Focus</div><div>-Angle</div><div>-Point of view</div><div>-Light <br><br></div><div><br><br></div>]]></description>
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         <pubDate>2016-11-14 18:43:58 UTC</pubDate>
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