How many of your Facebook “friends” are really friends?

How many of your Facebook “friends” are really your friends? For a long time, I have been curious to what friends on Facebook really means and it’s something that people don’t usually think about while going on Facebook. Going through every single person on my friends list was definitely a time consuming task, but it taught me a lot about how we use social media as a society. From what I can remember from middle school going a little into high school, the notion that having a large friends list made you seem “more popular”. For that reason, I had 1,028 friends, and from there, I conducted my experiment. Initially I did not think that many of my friends would be people I did not know based on what I see everyday on my timeline. Also, no one was harmed, because I conducted the experiment with my own account and only asked people I knew about their own friends as well.

I put each of my Facebook friends into a category: friends I have never talked to or met, friends I’ve spoken to at least once (or haven’t spoken to in a few years), and friends that I am close with (or have had at least 5 or more conversations with). My results were as follows: 319 friends I’ve never talked to or met, 499 friends I’ve spoken to at least once, and 210 friends I am close with. I then went through 5 random friends that I have never met or spoken to and looked through their timelines. After doing that, I looked through my own timeline, and found not one of their recent posts. For a little more data, I asked a few other people on what they have noticed about their Facebook friends. Ideally I would have liked to sit down with them and have them look through their friends list and write down their data, but that was not possible due to time constraints. First I asked my mother because I wanted a variety of age groups. She has 84 friends, all of whom are people that are family or those she is close with. I asked my one of my good friends who is female. She has 484 friends, but she told me that a few months ago she had around 2,000. She realized that most of those on her friends list were not her actual friends, and went through and deleted many. Then I asked one of my male friends, and he has around 1,200 friends. He says that even if he isn’t close with someone, he likes to keep them as friends for networking and other purposes.

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You can also sort through your friends by different categories such as work, college, hometown, high school, etc. Facebook tries to make your connections easier.

By analyzing my own Facebook friends, I found that I accepted anyone that friend requested me, without caring if I knew them or not. By asking a few of the people that I know about their Facebook friends, I learned even more about social media. Through my mother, I can tell that adults are more cautious about who they let see their online lives. Through my female friend, I can see that she too had many friends for the wrong reasons. Through my male friend, I understand how having a lot of Facebook friends can also be beneficial. Because of this project, I actually decided to delete the friends that I have never met or spoken to, but keep ones that I have only spoken to maybe once. I did this because you never know when you might need to speak to that person again. Also, many of us use social media as a distraction, and it is always interesting to quote on quote “stalk” people on Facebook. It isn’t about having the most amount of friends anymore, but it definitely keeps connections available if you have an abundant amount. Largely, we don’t use media for actual friendships, but to see what is happening in other people’s lives without having to personally talk to them.

By looking at the timelines of a few friends that I had never met, I also learned a few things about Facebook itself. None of their recent posts even came up on my timeline. It seems that the algorithms that Facebook has in place, keep my most clicked on friends a part of my timeline. The pages I visit on a daily basis are what stays on my timeline. Although, the majority of my timeline is pictures and different ads or news stories about how Taylor Swift finally showed her belly button. About 10% of my timeline on any specific day are of statuses, but I also think that can be explained by how people mostly use Facebook now. Facebook is used to update families with new pictures, link to other accounts or apps, networking, and group events. Twitter is one of the places where you can find most people actually writing out their “feelings”.

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Ads like this one (sponsored by Verizon), are a large part of my timeline.

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As well as different stories about pop culture based on different pages I have liked.

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Something that really caught my attention while gathering my results was Facebook’s new “Introducing Close Friends” option. It is as if Facebook knows that many people have a lot of friends, most of which are not close ones. They now allow you to star your closest friends, so that you see them more on your timeline. Facebook also warns you from time to time to only friend people that you actually know, because social media can be dangerous. That is why I took the time to delete those friends I had never even heard of.

So what is Facebook for? Everyone has a different use for it, and it changes all of the time. In terms of friendship, there are people who we are very close with, but many Facebook friends are people who we have only met once. It helps with networking and keeping connections throughout the years. The way Facebook is used tells us that we use media as a way to gain knowledge about other people, without having to actually speak to them. We can be friends on Facebook, but not say a word to each other in real life. Facebook lets us hide behind our computer screens and avoid conversations in person because everything you need to know is online. It definitely tells us a lot about how media has changed social relationships between people. I think this is also the same for other social media sites, such as Instagram or Twitter. Social media in general allows you to know more people without personally knowing them. In some ways having many Facebook friends can be positive, but also it can take away from real world interactions.

Analyzing Comments on YouTube

Most people assumed the development of the Internet would allow people to communicate in an environment where race didn’t play any role because of hidden identities. However, with profile pictures and usernames, people can assume the identities of other users on various social sites. One site that I’ve seen many people make assumptions on is YouTube. Many accounts on YouTube consist of only a profile picture and username, which people use to guess others identities. I believe these assumptions can lead users to post biased responses to comments on videos that can target the other persons ‘beliefs.’

This idea led me to develop the question; how do people respond to comments on YouTube videos based off of who they assume the commenter’s identity to be? In order to collect proper data, I had to specify which videos I was going to analyze. I wanted to choose controversial videos that most people know about, and which I could also relate to the topics we talk about in class. I decided on music videos that objectify women, since that is a big topic in class and in the entertainment industry. In order to gain diversity in my research, I chose a black male (2 Chainz), white male (Robin Thicke), black female (Nikki Minaj), and white female (Miley Cyrus) music artists.

I created three YouTube accounts, each with different identities. I didn’t want gender playing a role, so all of the identities were males. I created a black male named DeShawn Brown, white male named Connor Johnson, and Indian male named Kumar Patel. I proceeded with the research by commenting similar things for each identity on the music videos.The comments I posted were mainly about enjoying the videos and believing that the nudity was an artistic quality that the artists were entitled to include. I thought this would lead people to reply saying that I was basically saying its okay to objectify women. However, I didn’t get responses for any of my identities on any of the videos. This led me to change my research method to evaluating the comments that are currently on those videos, and determine whether or not people make assumptions on the identity of other users.

Before analyzing current comments on the music videos, I realized a pattern among the comments that I had posted through my fake identities. When I was signed in on Connor Johnson’s account, the comments that I posted through that account were the first ones in the comment section. However, when I was logged in on Kumar Patel’s or DeShawn Brown’s accounts, the comments I posted through those accounts came up later in the list of comments. I’m not sure if this is random, however, it does seem odd that the white male’s comments would be easily accessible through his account, while the others were harder to find for the users after they posted them. Of course, I only used three accounts, so this pattern can only be verified if found among a large number of accounts.




On the various videos, I analyzed the first two pages of comments. Overall, I have to say that I didn’t see many biased responses based off of what various users believed other users identities to be. While I did find a couple comments here and there with identities of users being an issue within conversations, the majority consisted of simply arguing over topics of the music videos.

Wrecking Ball, by Miley Cyrus, contained comments that mainly argued over the topic of Miley being a role model for many young girls. Most people didn’t feel that it was right for her to portray nudity to all of her viewers. I discovered on comment in which one user, 11219tt, assumes the ethnicity and beliefs of another user, Clayton (presented in the image below). The assumed identity of Clayton ended up being incorrect.


Anaconda, by Nikki Minaj, mainly consisted of comments about Nikki’s fake butt and boobs. They didn’t have much content to them or intellectual opinion, which is expected. I didn’t find any comments in which others speculated the identities of other users.

Blurred Lines, by Robin Thicke, had comments that fought over the topic of feminism. I found this odd because all of the other videos had objectification of women, but they didn’t have many feminists commenting on them. The screenshots I took were of two identities arguing that the video isn’t about rape. Both of these identities are of males. Both males are of different races, however, the responses to their comments are focused purely on their gender.



The last video I analyzed was Birthday Song, by 2 Chainz. Despite the fact that this video sexualized women the most, it was the most liked out of the four. This is mainly because 2 Chainz is known for his random and explicit videos. He has a specific audience, which means that the comments consisted of sarcasm and not many intellectual conversations. While most people talked about the lyrics in the song, one person decided to comment on race. You can see in the screenshot that a racist comment from Jon Snow led another commenter, Emanuel Lavan, to leave a response about his identity. The assumed identity was incorrect.


You can see that most people are incorrect when they try and assume what another person’s beliefs and race are through YouTube accounts. My research didn’t find as many speculations on identities as I believed there to be, which either means that people don’t look at race as much anymore, or I simply didn’t choose the right videos to observe. Also, while all of the music videos I chose had objectification of women, they all had totally different audiences and arguments. It seems that the comments section consists of a specific topic of argument, and people are usually too focused on that topic to worry about the identities of other users. If any assumptions were made in the comments section of the videos I evaluated, it was most likely unconsciously done.

Exploring Anonymity in Social Media

In this class I was required to read part of the book “It’s complicated: The Social Lives of Networked Teens” by Danah Boyd.  This book mentioned that people initially believed that the internet would lead to the end of racism and sexism as a whole citing the fact that people are anonymous online as the reason for its downfall.  However this book then explored why researchers didn’t believe that this would be possible, mostly due to the fact that people in essence bring their social circles with them when they interact with others online.  It was this book that inspired me to research the concept of racism, sexism, and anonymity in social networks.  My research question was: how would people be able to interpret the race and gender of an individual based upon simply reading the raw text of their most recent social media updates without being given any other information.

In order to explore and attempt to answer this question I decided that I would pick Twitter as the social media site that I would use due to the fact that it is the most text based of the current, popular, social media sites as well as the fact that it is one of the more actively used sites among my peers.  The method that I chose was to show these different pages of plain text to different people and asked them to determine the race and gender of the individual that the twitter account belonged to.  In order to make sure there was an even distribution of race and gender I chose to include 3 twitter accounts each from an Asian male, an Asian female, a black male, a black female, a white male and a white female.  These were all randomly chosen from the list of people that followed me on Twitter.  I also chose to include the 15 most recent tweets that fit the criteria of being an all text tweet (no pictures included) and does not tag another user in order to avoid including conversations.



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(Usable)                                                                                                         (Not Usable)

I also opted not to include emojis in order to give each page of tweets the same appearance.  Once I had picked the tweets that I would show to the guessers I chose to display them on a Word document with plain black text with each tweetappearing on a bulleted list where the only heading is “Twitter Account” and then a randomly selected number that compares to each twitter account.

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I selected these numbers by writing each name on a piece of paper and randomly picked each piece to determine the order.  When I went to interview the guessers I explained to them that they were looking at the 15 most recent tweets of an individual and they had to select a race from the possibilities of Asian, black, or white, and to guess gender as either male or female.  I did not tell the guessers that there was an even number of each race and gender and I didn’t let them see what they had selected after they had made a decision.  I then displayed the twitter accounts one at a time and didn’t switch to the next account until after the guesser had finalized an answer as to the race and gender of the individual.  I recorded this data in the form of a table where I had the twitter account number down the first column and the race and gender of each guesser along the top row of the table.  I then recorded the race and gender that they believed each twitter account to belong to.

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I then summed up the amount of correct and incorrect guesses as well as the amount of times that each guesser chose each race and gender.  In order to protect everybody’s privacy I only included information relevant to the experiment.  I chose to only display each twitter account as a number, race, and, gender instead of their actual name or twitter handle.  I also displayed each guesser in terms of their race and gender instead of their name.  I also only used Twitter accounts that were already set to private.

My hypothesis was initially that people would have a difficult time differentiating the race and gender of an individual based solely on the text of their tweets but after I had set up the experiment and created the word document I had to change my hypothesis.  I noticed that even within only the 15 most recent tweets an overwhelming majority of the 18 twitter accounts that I chose to examine had made explicit references to their own race and gender.  My hypothesis directly before beginning the experiment was that the guessers would be fairly successful in determining the race and gender of the individual owners of the twitter accounts.

What I found was similar to my hypothesis but with some very notable differences.  Among my responses there were 107 guesses that correctly identified race and gender out of 180 total guesses.  That correlates to a 59% success rate.  However, it is interesting to note that the success was not due to direct statements that identified race as I had assumed would be the case but rather due to “dialect” and “use of certain words” as one white male guesser noted.  He noted that this also held true for gender, specifically he said he identified males if they discussed a topic such as sports or females if they discussed a topic such as dancing or makeup.  Also nearly every single guesser identified that they went into the survey with a belief that they would be able to distinguish between white and black very easily but would struggle between Asian and white.  This means that among the people that I surveyed there was a belief that there existed a very serious cultural divide between black and white yet very minimal differences between Asian and white.  However there was no comment made about gender and when I asked one Asian male why, he responded with “I don’t know that just seemed like it would be easy”.  Not only do preconceived cultural differences exist between races but they exist even between people of the same race with different genders!  One white male noted something very important midway through his survey as he stated “when I can’t decide which answer it is my default is white male” and a black male said something similar as he stated that “when a tweet looks like something that I would think I assume it’s a black male”.  This resulted in skewed results across the board as white males generally had more male guesses than female guesses and more white guesses than Asian or black guesses.  This same pattern held true for the races and genders of the other guessers.  There was no clear distinction between the race or gender of an individual and the percentage of correct guesses.  In terms of answering my initial research question I believe that people are able to successfully distinguish the race and gender of an individual based solely on the raw text of their social media updates.  Relating this topic back to the initial Boyd reading that discussed anonymity my results provide evidence for the fact that individuals do, in fact, bring their social network with them when they go online resulting in a difference not only in who people communicate with but also in how they communicate with each other.

How Identity is Reflected Through Advertisements

Identity can be expressed through many mediums and based upon various aspects of the self. Race, gender, and class are common bases for identity. However, people also use other aspects of life to help define who they are. Identity can even be based off of commercial products. Take, for example, the way people dress. Most people choose their clothes to fit within their perceptions of themselves. As a result, when people shop, they buy products that reflect their identities. For our research project, we decided to look at how the products we shop for online are representative of our identities. How do the products we consume represent who we are? How do online retailers, like Amazon, learn about our identities through what we buy, and how do they use that information to appeal to us via advertising? What are the implications of seeing personally tailored ads online when we consider those ads as an interpretation of one’s identity?

To answer these questions, we researched the topics of identity through commerce and conducted a personal experiment. We began our research by examining the link between consumption and identity. We then focused on the specific examples of the Deadhead fans of the Grateful Dead and Nike products in Honduras. We also considered scholarship on how advertisers use knowledge about consumers’ identities to sell their products. For our experiment, we looked specifically at Amazon, the most popular online shopping site and a major advertiser on the Internet. We investigated whether ads shown by Amazon accurately reflect identity and how those ads could impact the viewer. Our analysis of our experiment’s findings draws on our research to consider how the Internet and the algorithms that track our spending habits affect the interactions between consumption and identity. Our analysis tries to illustrate what the link between consumption and identity looks like in the Internet age.

Our research on the interaction between consumption and identity included various articles that were all built on the assumption that the products we buy have meaning. Commodities have meanings attached to them. These meanings can be obvious – for example, the way that a Baltimore Ravens jersey means that the wearer is a football fan – or more subtle. As consumers, we use the meanings attached to products to reflect and strengthen our beliefs about ourselves, infer things about others, and identify ourselves as belonging to certain social groups. One way that consumers use commodities to define themselves and belong to a group is through consuming music.

Music, as a good produced by an industry, falls under the category of processed and profitable sources of identity. Many people use the music they listen to as an expression of who they are. In this way, music can form communities, strengthening that identity as the listener becomes not only a fan of an artist but a member of a larger group. This is because certain types of music are often associated with certain views and standards. As a result, many avid fans of a band are likely to share not only their musical interest, but their opinions on larger topics as well.

One prominent example where people connected through music was the “Deadhead” community of Grateful Dead fans. Politically charged lyrics combined with a sound appealing to people with those views and as a result followers of the Grateful Dead were like-minded people. The band formed such a popular touring act because of their very dedicated fan base. In turn, the fans felt that going to shows and being a Deadhead was an integral part of who they were. Here, commercial products, albums and concert tickets, are being purchased by people in order to realize their identity as fans. However, identity based on possessions and experiences created by other people may not be able to endure. When band member Jerry Garcia died, this community was in upheaval. How could these people go on living their lives as Deadheads without the band? Some members remained active in the Deadhead community, supporting the remaining members’ subsequent projects in order to hold on to this part of themselves. However, there were also people who left the community, who removed this part of themselves.

In the same way that consuming Grateful Dead music identified Deadheads with certain political views, our research about consumption and identity found that some products have complex political meanings attached to them. For example, the Garifuna, a community of black Hondurans, identify Nike brand products with similarly complex political meanings. Beginning in the 1980s, Nike advertisements associated Nike products with African American athletes and an image of masculinity linked with a kind of “inner city authenticity” (Tsing 165). Nike’s interpretation of black masculinity resonated with the Garifuna, who use Nike’s logo and products as a symbol for empowerment and economic success. Anthropologist Mark Anderson writes that ‘‘Among Garifuna in Honduras, the Nike swoosh circulated as a polyphonic icon of youth resistance, racial blackness, economic status and corporate power’’ (Tsing 165). The power of the Nike swoosh as a symbol can be seen in its use in varied contexts: Garifuna painted the symbol on the sides of taxis, houses, and even on rocks, and some tattooed it on to their bodies or shaved it into their hair. The Garifuna’s use of Nike products to represent a part of their identities is an example of how the goods we consume reflect and reinforce the ways we see ourselves.

The Deadheads and Garifuna might be considered what Sarah Banet-Weiser calls “consumer citizens” in her book Authentic TM. Consumer citizenship means expressing ideas about politics and identity through consumption. Banet-Weiser’s scholarship on consumption and identity points out an important component of the interaction between the two: the fact that brands and businesses are aware of consumers’ use of their products to express their identities and use that knowledge for profit. Brands sometimes choose to appeal to consumers’ identities and political views by using social activism as a means to advertise. An advertising campaign that uses social activism to sell products is called “commodity activism” (Banet-Weiser 16). A prominent example of commodity activism is Dove’s Campaign for Real Beauty, which uses ideas from the feminist and body positive movements to sell Dove products. When we shop online, we interact with more than just advertising campaigns like these that may or may not be tailored to our viewpoints. We also see content generated by algorithms whose job it is to show us products that appeal to us. These algorithms’ ability to personally tailor our experience with advertisements means that brands and advertisers could use the interplay consumption and identity for profit more powerfully than ever before.

During our personal experiment part of the research process, we looked into how online shopping, particularly on Amazon, influences the ads shown to you on the Internet. We wanted to know how these ads reflected the identity of the user. We hypothesized that at the end of the experiment, the ads would form a fairly complete picture of the other user. For our experiment, we would trade computers for ten minutes every day for three days. During that time, we would search for products we found related to us. Then, in our daily Internet usage, we would screenshot any Amazon ads we saw. It was easy to ensure that no one else would be disturbed by our experiment; we would be the only ones to see the advertisements.

While we had expected the ads to show us many different items related to the items we had viewed, we found that Amazon almost exclusively showed us ads of the exact products we had previously clicked on. This has led us to conclude that Amazon does not try to assume what we would and would not like, it simply regurgitates our shopping history back to us. It was also interesting how quickly the new periods of searching changed the ads we were shown. After each period of searching, the ads of products the other person had just searched for replaced the ads of products from the search before. The result of this was that we not shown anything near a generalization of the things the other person was interested in. We saw nothing more than their most recent searches.

Our experiment found that Amazon’s algorithms are not sophisticated enough to make judgments about a user’s identity through the goods they consume, at least not to the point that Amazon can recommend new products to the user that appeal to their sense of self. We proved Amazon searches are not a definitive picture of someone’s identity, despite attempts by advertisers to gather information this way. But even though Amazon’s advertising capabilities have not yet progressed to that level, the ads Amazon shows us are still very relevant to our identities. When we went online and the ads tried to sell us products that we had already expressed interest in by clicking on them in Amazon, that was an algorithm used to determine who we were and what we might purchase. These ads show us the same products over and over again because it has been concluded that if you already viewed those products, you are more likely to buy them. Being shown the same ads repeatedly reinforces an online consumer’s identity. The idea that seeing advertisements for the same products strengthens our view of ourselves is similar to Eli Pariser’s concept of filter bubbles that we discussed in this class. We are being shown identical products over and over instead of a representation of all of the products on Amazon. This means that Internet ads are repeatedly reinforcing a constructed interpretation of the user’s identity. As time goes on and the user is bombarded with these types of ads, they may come to believe in that identity.

All in all, our project sought to understand how the Internet and algorithms that track consumer behavior might strengthen the relationship between consumption and identity. From the limited findings of our personal experiment with Amazon advertisements, we believe that Internet algorithms have not yet progressed to a point where they are able to get a clear picture of a consumer’s identity and tailor the individual consumer’s online experience accordingly. However, a broader experiment might find that Amazon’s algorithms are more sophisticated than they have been in our experience. Whether through advertising filter bubbles or through more complexly constructed advertisements geared towards an individual’s identity, the Internet is causing the relationship between consumption and identity to evolve.



Screen Shot 2015-03-08 at 5.11.24 PMThe search history on the left shows Chris’ searches for laundry detergent and fabric softener. On the right, Amazon showed Emma an ad through Facebook for the exact fabric softener that Chris had searched for.

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Emma’s browsing history on the left contains all three of the items pictured above in an ad on AZ Lyrics.


Works Cited

Banet-Weiser, Sarah. Authentic ™: The Politics of Ambivalence in a Brand Culture. NYU Press, 2012. Print.

Duffett, Mark. Popular Music Fandom: Identities, Roles and Practices. New York: Routledge, 2014. Print.

Pariser, Eli. Beware Online “Filter Bubbles.” TED. Mar. 2011. Web.

Tsing, Anna. Supply Chains and the Human Condition. Rethinking Marxism: A Journal of  Economics, Culture & Society. London: Routledge, 2013. Print.

Zimmerman, Ian. We Are What We Consume. Psychology Today. New York: Sussex Publishers, LLC, 2013. Web.

The Relations Between Facebook Users and Targeted Advertising

It is well known that Facebook, like many websites, shows advertisements on its pages presumably to earn ad revenue. However, recently it has been showing ads on users’ News Feeds as well, and this has become an object of criticism for many people. After hearing many valid complaints about this move and deliberating my research topic, I decided I would look into users’ thoughts and opinions on News Feed ads. To this end, my research questions are: What do Facebook users think about the ads they see and what do they do with them? What does this information tell us about the role of targeted advertising in our online culture?

The Ads
A typical News Feed advertisement on Facebook. (Ignore the ads on the right side.)


My method of gathering this information was to first post the following prompt on my Facebook page:

Research Question Blog Size


My intention in asking those questions was to collect enough detailed data to draw conclusions on the relationships between users and ads. When I only received eight responses over four days, I was forced to conduct live interviews while asking the same questions. The interviews gave me four extra responses. I made screenshots of the responses I received on Facebook, and I recorded all of my responses in a separate word document. I also removed all identifying information of the responders from both modes of documentation. In this post, I will analyze the responses and discuss notable patterns as well as outliers. Unfortunately, I forgot to ask for permission to quote on my first prompt, and when I asked for people willing to let me quote them, only three gave permission. When I began the experiment, I was fully expecting all of the responders to be hostile or indifferent to the ads on their News Feeds. However, when the survey was done, I had received a surprising variety of opinions on the ads.

Before we look over the results, it’s worth noting that one responder simply didn’t see any ads on their News Feed because they didn’t use Facebook enough. Therefore they couldn’t answer any of my questions. From here we will examine the other eleven effective responses.

First, we will go over the predicted responses: those who disliked and/or ignored their ads. Of those eleven responders, only one explicitly reported ever clicking on any ads. Four people (including the one just mentioned) ignored most ads they saw because they predictably didn’t care enough to delete them, and another four either told Facebook to remove the ads or installed AdBlocker to prevent them from appearing altogether. Finally, ten out of the eleven responders knew that Facebook specifically gave ads to them based on a combination of web activity, pages visited, and geographic location.

A responder who uses AdBlock.
A responder who uses AdBlock.

Based on the observations so far, the majority of Facebook users seem to know that their ads are targeted towards them. As one responder stated, “It is more effective to have ads tailored specifically to personal interests.” Another responder even expressed discomfort at Facebook using their information to send them ads, so Facebook’s marketing can be seen as an invasion of privacy for some. I can also say that many people simply ignore the ads they see while another, similar percentage of people, actively try to remove them. Precise numbers can’t be estimated due to my small sample size, but my hypothesis was correct with most responders. Most people are not interested in what the ads show them, so I believe the ads don’t affect them much aside from being inconveniences. The most interesting results, though, are the unexpected ones.

One responder noted that they actually liked the ads for their design and didn’t remove them because they wanted to keep them for future reference. At this point I started to gain insight on other sides of advertising. Sometimes ads do help people find products they’re genuinely interested in, and in that case ads would benefit the user, the company, and Facebook. There’s a transfer of power there, just by clicking on the ad. Clicking the ad means giving attention to what is being shown, and the ad therefore can work with the user’s mind to sell a product. Still, even though the ad holds more power with the user’s attention, the user ultimately has agency in whether they follow the ad’s suggestions or leave and go about their day as usual.

Also, while most responders said ads were annoying or shallow, only one said they were actually offended, and that was because the ads were stealing copyrighted work. It’s possible that most of Facebook’s ads are moving away from offensive content like stereotypes or sex appeal, although one responder has said those rare ads still exist. Ads that are offensive, whether through shallow tactics or through defacing what users enjoy, would alienate too many people. We have to examine one last response to get the full picture, though.

The last responder, surprisingly, said that though the ads are annoying, they keep them on because they want Facebook to be free. This response caught me off guard, but it makes perfect sense. I did some research online, and Facebook gets more than 80% of its revenue from advertising (as of 2011). Some people are willing to put up with ads if that’s what it takes to keep Facebook free. It’s understandable that this responder is concerned about removing ads. If most people ignore or remove ads, then Facebook probably earns revenue just by having ads appear on users’ screens. Still, the targeted nature of ads implies that Facebook has motivations for enticing people to click on ads. Facebook’s algorithms try to send ads to those who are most likely to click on them, although there are clearly flaws in the system if the ads are turning many people away.

Something I didn’t expect to turn up was “content mills” like Upworthy and BuzzFeed. As one responder said, “Stuff from BuzzFeed and Upworthy spread like wildfire” partly because of their use of “click-baits,” and while they’re not exactly ads, their method of spreading ideas is reminiscent of ads. Though these sites don’t ever market products, they may have some unsettling implications. Content from “content mills” doesn’t just entice people to click on the link; it subtly makes them agree with some idea it’s promoting. If those tricks are used to advertise a product, targeted ads would become more prolific and convincing. People don’t like to have products aggressively marketed towards them; hiding the product behind an article that “agrees” with the user could be much more effective. When I noted earlier that a successful ad benefits the user as well as the companies, that may be something an ad touts. It would seem as though it’s helping the user. As of right now, ads don’t have the same attracting effect that content mills have, but there is nothing stopping advertisers from making it so. That would likely generate more revenue for Facebook, but then ads would become far more than annoyances for most users.

A responder who noted Buzzfeed and Upworthy.
A responder who noted Buzzfeed and Upworthy.

For the present, Facebook’s targeted ads are its way of generating revenue and keeping the service free. There is a clash of interests though. Targeted advertising, while successful in some instances, can be ineffective or even offensive toward its intended audience. Facebook only focuses on what we seem interested in, and it uses that data to show the ads we’re most likely to click on. For those who ignore or remove ads, the ads are annoyances. For those who use the ads, they can reflect or even shape their interests. There is a reasonable chance that ads can become more effective and insidious, though. For now, my evidence suggests that targeted advertisements, while shallow and annoying, are a necessary tradeoff for a free social network. Beyond generating revenue, the ads may influence some decisions among users, but for many people the ads don’t currently do much. That being said, it is wise to keep an eye on how prolific and convincing the ads are becoming.