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Do photo filters affect the amount of likes received on social media?

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We studied 20 social media accounts with about 5,000 followers who each posted 3 times a week.

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We randomly picked the 20 social media accounts who considered themselves social media influencers. All of them agreed to be a part of this experimental study in which we could chose if they could use filters on their posts or not.

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During a 1 month period, 10 of the social media influencers were allowed to use filters on their photos. The other 10 social media influencers weren't allowed to use photo filters during the time period.

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The explanatory variable was whether or not the social media influencers were allowed to use filters on their photos during the 1 month period.

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After the 1 month period, we collected the total amount of likes for those who used filters and those who didn't use filters in order to see if filters had any effect on the total amount of likes.

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We randomized the types of accounts to make sure that their were a variety of different types of social media accounts who all had different goals than each other. Potential lurking variables could include advertising, types of posts, video or photo posts, and the platform of social media used.

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The control group is the group of 10 people who don't use filters for their social media photos.

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We can't blind the social media influencers because they know if the can or cannot use filters on their photos. There is not double blind because we assign them whether or not they can use filters.

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It would have been difficult to do random block design. The social media accounts were assigned whether they were allowed to use filters or not which which we decided to do the match pair design with.

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A matched pair design was used in this experiment because there are different types of social media influencers (bloggers, photographers, journalists. etc.). This was easy to do since there are many influencers who do similar things on social media and it was easy to assign them to different groups.

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Since we used a matched pair design we didn't use crossover design because the results are more reliable when the influencers are assigned to use filters or not to use filters. A crossover design would have been too complicated and hard to interpret what the results meant.

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Our sample size was 20 total subjects and the margin of error is 22%. This is a high margin of error and it could be lower if their were more test subjects. But, it is hard to find social media influencers who let us control their ability to use filters or not

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I want to do this experiment another time when the all of the accounts have about 10,000 followers. If the results of the second experiment are similar to the first, then the results will be more valid and the results would stand for a large range of total followers. The next experiment would
also include more instagram accounts in order to decrease the margin of error in the results.

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After 1 month, we counted the total amount of likes for the 10 people who used filters on every photo and the total amount of likes for the 10 people who weren't allowed to use filters on their social media posts. We found that the people who used filters did not receive as many likes as those who didn't use filters because many people don't like how filters take away from the original photo.

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9 of the 10 people who didn't use filters had more likes than any of the social media accounts that did use filters. These accounts also gained more followers than the accounts who used filters. Because of this, we believe that this is statistically significant. Those who don't use filters have a better chance at getting likes.

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The results of our study was sent out by social media platforms to all of their social media influencers. The ones who chose to listen and to not use filters showed an increase in likes and followers than those who didn't. Now it is a known tactic for all growing social media accounts.

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We paid each social media influencer $1,000 to participate in our experiment. For 20 accounts, our total cost was $20,000.