Birds of a Feather: How TV Fandoms End up as Twitter Echo Chambers

Disclaimer: The contents and opinions of this blog post do not represent the views or values of Honours Review as a publication.

In today’s social media dominated world, platforms like Twitter are not only there to allow users to express themselves in 280 characters. On a scale achievable only by a multi-billion company, people can now turn to tweeting as a way of connecting over-shared preferences for their favourite media, with television emerging as the winner. Here is where we see the emergence of a golden rule: fans of the same TV programs prefer opinions which support their own (4). This phenomenon, known as opinion homophily or echo chambers, deserves attention as the number of fandoms increases in this triumphant TV era of content streaming platforms like Netflix. But why exactly do TV fandoms on Twitter have a tendency to form homophilic echo chambers? 

The Power of Hashtags

Perhaps the most apparent link between online fandoms and homophily is the way Twitter’s technological affordances – the media platform’s characteristics determining what users can and cannot do – make it easy for TV fans to connect with similarly-minded people. Functions such as likes, retweets and mentions allow fans to start a friendly chat with a fellow fan whose opinions they find agreeable (10). What’s more, some affordances can be used to broaden online interactions from dialogues into conversations by involving other fandom members. A like or a retweet is limited to displaying individual support of a Twitter message. Referring to someone by their @username, however, invites responses not only from the mentioned user, but also from the fan audience as a whole (3). As fans seek out similarly-oriented comments within these responses to reassure themselves in their opinions, fandom echo chambers are created. 

Twitter’s filtering tools, like hashtags and user-blocking, also allow fans to avoid opinions they know they would disagree with. As a result, the hashtag as a keyword-filtering feature often ends up polarising the fandom by visibly dividing it into fan armies defending their favourite TV couples or characters. Twitter discourse on the show Game of Thrones, for example, is visibly divided into supporters of the main characters who might end up on the coveted Iron Throne. Name-based hashtags – #DaenerysTargaryen, #JonSnow and #NightKing – trend on Twitter like clockwork every time a new episode is aired, with their respective supporters largely ignoring the content marked by the other side’s hashtag. Additionally, according to research by Bruns and Burgess (1), hashtags can cultivate homophily within themselves as the top opinions can become known and followed fandom-wide. Isolating themselves even further, some Twitter users also remove the potential for others to directly speak against their views: taking advantage of the “increased control given to consumers by the new media” (4), fans can actively block their opposition to form uninterrupted echo chambers. 

Friend or Follower?

Beyond technological features, user-constructed social networks on Twitter are the backbone of discourse spaces where fan opinions can be expressed unopposed. Research suggests that users primarily use social media to maintain real-life friendships and only secondarily to generate new ones (8). This implies that an individual’s fandom related activities are often witnessed first by their close acquaintances. Receiving agreement or even a simple lack of counter-arguments from their “inner circle” then provides a sense of approval to the fan, empowering them to spread their views to the rest of the fandom. Thus, friendship bonds contribute to the creation of personal online echo chambers.

The social ties between members of TV fandoms can range from personal to anonymous as fans impose an opinion to be echoed by their followers. These followers are people who have chosen to see the fan’s every post, retweet and mention in their timelines. Accordingly, the fan’s mental perception of them becomes the individual’s “imagined audience” which does not necessarily represent the actual reality (6). In fact, investigations like Litt and Hargittai’s 2016 study have revealed that online social media users commonly imagine their audience simply as “people who they thought would like or agree with their posts” (5). This perceived lack of opposition leads many TV fans to format their opinions as if they are the only valid ones, inviting online homophily. 

Echoes Across Time and Space

With friends, followers or alone, the immediacy of viewing a beloved TV show as it is broadcasted and simultaneously commenting about it via Twitter often leads to reactive homophily among live-watching fans. Multitasking by using a phone or computer while watching TV, known as second-screen viewing (9), results in many fandom tweets being posted while the episode is airing. These emotionally charged reactions frequently exhibit echo chamber properties, since shows are constructed to broadly evoke certain emotions, such as excitement or shock, in every viewer. Thus, increased Twitter user agreement is likely, compared to the diversity of informed opinions between fans who watch and comment after the initial airing of the episode. Additionally, the fandom being more present on Twitter while the show is “live” distributes user attention unevenly. The trending or initially most popular opinions are favoured, threatening to overshadow any alternative perspectives added later on (11).

Interestingly, TV lovers in close physical proximity, although connected in the global media space of Twitter, often still gravitate towards each other to form regional fan groups (7). As this shared characteristic becomes another bond between them, such communities are especially vulnerable to becoming echo chambers. Besides geocultural similarities drawn upon when constructing opinions, there is also the social pressure to fit in among peers by not opposing the dominant perspective of the group. This effect increases when a shared language, other than the ever-present English, is used to communicate within the cluster of fans, acting as an additional isolating barrier between their opinions and those in other languages (2).

Conclusion

In the end, the opinion homophily of Twitter TV fan communities appears to be a multi-step process. Firstly, the platform provides built-in tools, like hashtags, for fans to connect and distance themselves from other opinions. Secondly, the fans’ social networks and imagined audiences influence the presentation of their views as ones to be echoed. Finally, differences in time and space invite fans to interact in environments favourable to homophily. 

References:

1. Bruns, A., & Burgess, J. (2012). Researching news discussion on Twitter. Journalism Studies, 13(5/6), 801–814. https://doi-org.proxy-ub.rug.nl/10.1080/1461670X.2012.664428 

2. Hale, S. (2012). Net increase? Cross-lingual linking in the blogosphere. Journal of Computer-Mediated Communication, 17(2), 135-151. doi:10.1111/j.1083-6101.2011.01568.x

3. Hemsley, J., Stromer-Galley, J., Semaan, B., & Tanupabrungsun, S. (2018). Tweeting to the target: Candidates’ use of strategic messages and @Mentions on Twitter. Journal of Information Technology & Politics, 15(1), 3-18. https://doi.org/10.1080/19331681.2017.1338634

4. Karlsen, R., Steen-Johnsen, K., Wollebæk, D., & Enjolras, B. (2017). Echo chamber and trench warfare dynamics in online debates. European Journal of Communication, 32(3), 257-273. doi:10.1177/0267323117695734

5. Litt, E., & Hargittai, E. (2016). The imagined audience on social network sites. Social Media and Society, 2(1), 1-12. doi:10.1177/2056305116633482 

6. Marwick, A., & Boyd, D. (2011). I tweet honestly, I tweet passionately: Twitter users, context collapse, and the imagined audience. New Media & Society, 13(1), 114-133. doi:10.1177/1461444810365313

7. Takhteyev, Y., Gruzd, A., & Wellman, B. (2012). Geography of twitter networks. Social Networks, 34(1), 73-81. doi:10.1016/j.socnet.2011.05.006

8. Vallor, S. (2012). Flourishing on Facebook: Virtue friendship & new social media. Ethics and Information Technology, 14(3), 185-199. doi:10.1007/s10676-010-9262-2

9. Van Cauwenberge, A., Schaap, G., & van Roy, R. (2014). “TV no longer commands our full attention”: Effects of second-screen viewing and task relevance on cognitive load and learning from news. Computers in Human Behavior, 38, 100-109. doi:10.1016/j.chb.2014.05.021

10. Young-shin, L., & Lee-Won, R.J. (2017). When retweets persuade: The persuasive effects of dialogic retweeting and the role of social presence in organizations’ Twitter-based communication. Telematics and Informatics, 34(5), 422-433. https://doi.org/10.1016/j.tele.2016.09.003.

11. Zubiaga, A., Spina, D., Martínez, R., & Fresno, V. (2015). Real-time classification of Twitter trends. Journal of the Association for Information Science and Technology, 66(3), 462-473. doi:10.1002/asi.23186.

Personalising the World: The Implications of Curated Media

Disclaimer: The contents and opinions of this blog post do not represent the views or values of Honours Review as a publication.

Introduction: The Public View on Personalisation

Song recommendations, video suggestions, related articles – these are just some of the curated features we have come to rely on when using platforms like Spotify, YouTube and online news sites. All of these strategies for making us consume more and more media material draw upon the much-debated concept of personalisation: tailoring content to suit personal preferences. It might sound luxurious, but there are darker consequences for individuals and their communities indulging in the custom-made appeal inherent to many aspects of today’s world.

Ironically, a reflection of society’s worries about online personalisation’s negative effects is often most visible in online environments which employ different methods of personalisation, such as news sites. Wired claims companies like Google and Facebook are “violating our free will to choose the information we want” (2); Forbes publishes articles titled “Digital Privacy: Brands Figuring Out Where Personalization Gets Creepy” (5). When navigating opinions like these, readers should think critically about the many invisible ways that music, news and video content is curated for them on an everyday basis. Entrusting the personalisation of one’s information and entertainment to media companies and algorithms: is it a violation of the natural order or simply a convenience of technological development?

Catering to the Individual

Almost every website and media producer we turn to for content uses some type of curation not only to provide us with the song or video we were originally searching for, but also to keep us browsing other options for as long as possible. After all, our attention translates into their profits when we are exposed to on-site advertisements or pay our subscription fees. Media giants like Netflix are at the forefront of innovating strategies for learning each viewer’s preferences and accordingly crafting their binge-watching and Netflix browsing experiences. It is not just that different viewers will be offered different content: now, even the thumbnails for the same shows are customised based on individual viewing history (1). Of course, the millions of users to learn about and tons of screenshots to choose from for the most fitting thumbnail make this job impossible for humans to manage without the help of algorithms. But how accurately can a machine know us and predict our tastes?

When it comes to personalisation-specific algorithms, Spotify can be seen as the contemporary expert. Collecting and analysing mountains of data, the streaming service categorises listeners according to their taste profiles and then makes playlists like Discover Weekly – composed of songs you have not listened to, but which are supposed to fit your preferences. It is certainly an effective method for making the listener feel catered to, but it might also contribute to the depersonalisation of humans as complex beings who change over time, perceiving us more like machines to be figured out and kept satisfied. Internet activist Eli Pariser’s notion of the filter bubble – a state of intellectual isolation resulting from algorithm catered content (6) – is a related phenomenon that might not seem too serious regarding our preferences for music or TV series. Applied to news consumption or online political participation however, it raises concerns about the convenience of personalised content removing the necessity for the individual to explore, grow and change their perception of the world.

The Curated Community

Considering human evolution and development of technology, we might look at personalisation algorithms as just the newest disruptive element in the history of our media consumption. The “older media” of radio, broadcast TV and newspapers now have more attractive alternatives, respectively Spotify, Netflix and curated online news feeds. While this has undoubtedly been beneficial for many us, as we are free to access niche content any time, any place, often for lower prices, there are also losses to the broader society stemming from these changes in media use. The physical presence of a medium like television in households across the world has historically been tied to the family and community bonding functions a TV screen can fulfil (3). Now that we can view TV content on our phones, computers and tablets instead, there is reason to worry about the extent to which personalised media can bond community members rather than emphasise their differences and thus isolate them.

The idea of our belonging to a local community being limited by the isolating effects of media personalisation draws upon media theorist McLuhan’s popular concept of the “global village” – the world tuned into a village by technology, which enables information to move far and quickly (4). It is now much easier to be exposed to content from across the world whose niche characteristics, as identified by algorithms, match your preferences, where before one might have had to put in more effort to search for fitting content closer to home. Still, content in local newspapers, news and radio channels is also personalised, albeit in less detail, for us as members of the local community. Therefore, since many people continue to consume both global and local content, for example, visiting local concerts as well as going abroad to see your favourite artist perform, perhaps the community bonds are simply adjusting instead of disintegrating as feared.

Conclusion

A shift can be perceived in the counter movement to the potential self-isolation brought on by having your tastes constantly catered to. This opposition is the way we use our personalised content to represent ourselves on social media – a behaviour rooted in human history and nature, thus denying power to the argument that personalisation leads to humans being perceived more as machines to be figured out. Similar to how the content of your bookshelf and the ability to frequent opera houses was representative of your social status centuries ago, nowadays, the pages we follow on Facebook and the Spotify playlists we share with our friends are indicative not only of what we like, but also how we want to and will be perceived by others.

It does not seem that personalisation can be classified as a violation of human bonds as much as an agent of change, but it cannot be naively viewed as a no-strings-attached technological convenience either. Instead, the effects and future uses of personalisation depend on how we will balance the interactions between the algorithm and the human mind, as well as between the media company and the media consumer.

Bibliography:

1. Barton, G. (2018, November 21). Why your Netflix thumbnails don’t look like mine. Vox. Retrieved from https://www.vox.com/2018/11/21/18106394/why-your-netflix-thumbnail-coverart-changes.

2. Kaushik, P. (2014). Tomorrow’s Internet: A world of hyper-personalized tribes?Wired. Retrieved fromhttps://www.wired.com/insights/2014/03/todays-internet-world-hyper-personalized-tribes/.

3. McCarthy, A. (2001). Shaping public and private space with TV screens. In Ambient television: Visual culture and public space (pp.117-153). Durham: Duke University Press.

4. McLuhan, M. (1987). Letters of Marshall McLuhan. Oxford: Oxford University Press.

5. Newman, D. (2018, March 20). Digital privacy: Brands figuring out where personalization gets creepy. Forbes. Retrieved fromhttps://www.forbes.com/sites/danielnewman/2018/03/20/digital-privacy-brands-figuring-out-where-personalization-gets-creepy/#668ddae243a7.

6. Pariser, E. (2011). The filter bubble: What the Internet is hiding from you.New York, NY: Penguin Press.