Social media is heavily influenced by algorithms. For example, the Facebook feed algorithm, from what we know about it, is based on what you and your friends are liking, posting, and doing on the platform (and perhaps even ‘people like you’ that Facebook is data mining). Many social media algorithms are designed around homophily. And algorithms theoretically are value neutral. If someone consumes and produces criminal content, the algorithm will try to be helpful and guide the user to relevant criminal content. The algorithms are just following what they are programmed to do.  algorithms can equally encourage content around positive civic responsibility, if a user has displayed a preference in that direction.

To be critical about algorithms, we do have acknowledge the advantages and disadvantages of algorithm proliferation. For example, some algorithms are designed for safeguarding and this can be a real positive. There might be algorithmically-based filters for Internet searching or video delivery specific to kids for example. If a child has a profile on Netflix which is specifically set to Netflix’s child setting, then by the algorithm’s definition, they are not supposed to receive content that is age inappropriate. This tends to work in practice. Though, if content is inappropriately categorized, the algorithm would of course just follow its rule-based rubric instructions and would guide kids to inappropriate content as well. So humans are very much part of this process and if errors occur, then not having humans in the loop can partially be attributable to some of the issues of whether algorithms break down in these instances.

Ultimately, the algorithms driving social media are what are called ‘black box algorithms’. These can be defined as algorithms that are generally proprietary, and which are open-source. The algorithm is meant to be private in terms of its design and operation and documentation is not made publicly available, nor is data made available in terms of the decisions made by the algorithm. In this way, black box algorithms are also similar in that we can only infer particular aspects of the algorithm based on observing the algorithm’s behavior ‘in the wild’.

The study of social media has great promise, but we always need to understand its limitations. This sounds rather basic, but it is often not reflexively thought about. Though social media is not as shiny as it was several years ago, the zeitgeist still persists and it often clouds our ability to frame what it is exactly that we are doing with all the social data we have access to.[1] Specifically, if we use Twitter data, it is not enough to just leave research at the level of frequency counts (top hashtags, top retweets, most engaged with comments, etc.). David De Roure [2] warns that this type analysis of social media misses the social aspects of web technologies. Ultimately, social media spaces are sociotechnical systems and the social that is (re)produced – like face-to-face communication – is highly nuanced. I think that it is fundamentally important for researchers of social media data across the disciplines to think critically beyond the literal results of brute force machine learning. Rather, this is an opportunity for us to ask large and important social questions. My point is epistemological in that I think it is important for our results to contribute to our understanding of these social questions. This is not to say that quantitative methods such as natural language processing, n-grams (and other co-occurrence methods), and various descriptive statistics are not important to the study of social media. But, rather, they are often the starting or mid point of a research project. In my work, Big Data analytical models provide a great way to get a birds-eye view of social media data. However, they cannot answer social questions as such. However, these methods are valuable to, for example, grounded theory approaches, which can help produce valuable research questions or social insights. Additionally, the mixing of methods this encourages is exciting as it provides opportunities for us to innovate new research methods rather than trying to fit traditional research methods (though doing this is valuable of course too).

[1] Ramesh Jain in his talk at the NUS Web Science & Big Data Analytics workshop puts this as data being everywhere and that we have access to billions of data streams.

[2] In his talk at the NUS Web Science & Big Data Analytics workshop (December 8th, 2014)

“Most mass-entertainments are in the end what D.H. Lawrence described as ‘anti-life’. […] These productions belong to a vicarious, spectators’ world; they offer nothing which can really grip the brain or heart. They assist a gradual drying up of the more positive, the fuller, the more cooperative kinds of enjoyment, in which one gains much by giving much.” – Richard Hoggart, The Uses of Literacy

A major argument of Hoggart’s The Uses of Literacy is that mass media often let down the masses. Rather than bringing knowledge, they “belong to a vicarious, spectators’ world”. In collecting my thoughts for a Hoggart panel at Goldsmiths, University of London, I wondered whether Hoggart would see Twitter, Facebook and YouTube as “anti-life”? Are tweets egocentric and bombastic? Are Facebook posts self-important and overblown? Social media is unique in its interactivity and global reach. Re-reading Hoggart, I wanted to explore how social media challenges Hoggart’s binary between the brain-gripping and cooperative as social media can be both ‘mass entertainment’ and a ‘cooperative kind of enjoyment’ that also may produce new forms of democratic knowledge? Social media literacy may also be giving us new forms of knowledge production and consumption.

Hoggart argued, “It is not easy to find a decent platform without becoming occasionally priggish and portentous. But the present situation offers few grounds for satisfaction.” One could argue Hoggart’s words are just as true for social media today. The Goffmanian “front stage” aspect of tweets often bring out the priggish, though less the portentous. Social media places a temporal priority on the absolute present, which often tends to be egocentric and the self-presentation aspect of it often encourages inflated self-presentation. However, the fascinating thing about social media is they need not. They can quickly disseminate information and knowledge on everything from pandemics to disasters and can rally people to participate in social movements.

This interactivity is important. However, much of social media is not interactive. We often consume YouTube videos without commenting or sharing or posting response videos. In this sense, Hoggart would likely argue that “Charlie bit my finger”, “The Gummy Bear Song” and “Gangnam Style” are what he calls a “hypnosis of immature emotional satisfactions.”

One of the interesting aspects of Twitter I highlight in my book is it is uniquely simultaneously “banal” and “profound”. Hoggart would argue that these are not “serious” media. But, mass social media platforms such as YouTube host new forms of knowledge dissemination ranging from TED Talks to statistics professors explaining ANOVA.

Bringing this back to The Uses of Literacy, if library checkouts are not increasing (Hoggart uses this metric), is the production and consumption of social media (especially article sharing) increasing literacy? The whole notion of peer pressure to read what is circulated in one’s network adds new ways of seeing how the social operates in terms of literacy (especially through the ability to engage in comment-based dialogue with peers about that article in social media – i.e. a thread of Facebook posts and even linked videos – a truly multimedia literary engagement!)

Also, the consumption of knowledge articulated in a social media-friendly form (from infographics to YouTube videos) can cross class (a topic Hoggart is of course deeply interested in). These social media constitute new forms of literacy. TED Talks, for example, according to Alexa statistics are more viewed by women and are viewed at significant levels by viewers with no college education (though viewers with postgraduate degrees are far more likely to consume TED Talks).

As Stuart Hall notes, Hoggart saw culture “as the practices of making sense”. I think that rather than being “a vicarious, spectators’ world”, social media presents new opportunities to make sense of the social as well as for literacy: learning about different world views and reading things one would not normally come into contact with. Also, we increasingly interact with our peers on social media when they share articles on our feeds or profiles. Though a grave warning of Hoggart’s still very much applies to literacy and social media. The commercialization of mass media is just as much relevant to social media today as it was to Hoggart in 1957. Though not an “affluent debate” like it was in Hoggart’s time of writing, commercialization has a real impact on social communication on social media. Promoted tweets, targeted ads, and the infamous Facebook mood experiment all signal how knowledge production and consumption on almost all social media remain mediated by commercialization. Though not a vicarious, spectators’ world, social media remain subject to larger corporatizing media forces which have been longstanding.

A recent application of Big Data which has become understandably controversial is the Facebook experiment, where Facebook data scientists manipulated the feed content of selected users to include only positive or negative feed content. I have previously written about this.

The Guardian’s exposé on the U.S State Department’s PRISM project—which collects data from large technology companies— clearly highlighted the footprint users leave behind when utilizing the Internet. While this particular scenario represents a more extreme and some would argue unethical application of Big Data Technologies, the Facebook experiment reminded many of us why we spoke out about data privacy and PRISM. While many Internet users are aware of the trace data created via online interactions, the power and potential of this information when collected, aggregated, and analyzed is enormous and often easy to forget. The Facebook experiment speaks to the capability for nongovernmental entities such as corporations to easily access information that was previously not available nor analyzable. This type of information, paired with the right technology, can lend a unique glance into a person’s life and ultimately lead to more advanced insights directed towards a person’s interests, hobbies, activities, work, and more. This can be a welcome development in some contexts (e.g. those who opt into health behavior change interventions to quit smoking or lose weight).

However, most of the time, online footprint data (derived from platforms such as Twitter and Facebook) are used to facilitate personalized and targeted advertising (Silberstein, et al. 2011) at best and hyper-surveillance at worst. Some do not have a problem with this use of personal data (as a trade-off for ‘free’ services such as Facebook). Others, see the Facebook experiment as yet one more reason to either minimize their use on the dominant social networking site or quit altogether.


Silberstein, A., Machanavajjhala, A. and Ramakrishnan, R. 2011 ‘Feed following: the big data challenge in social applications’ Databases and Social Networks: ACM.

When we think of 10th birthdays, we think of youth and the cusp of tweenhood. But Facebook at 10, like many technology companies, is seen by some as an octogenarian. Social media technologies like the ephemeral snapchat are seen as nubile and exciting while Facebook is seen as part of an old guard status quo. Whether one loves or hates Facebook, the medium has become part of everyday life for many across the world. It has developed a gargantuan user base of 1.23 billion (passing 1 billion in 2012‎ and nearly a billion active mobile users). And one third of US adults get their news from Facebook. To say you are ‘Facebook friends’ with someone is an understood relationship. In other words, Facebook is part of many everyday lives.


Ultimately, Facebook has tremendous influence on what content is being consumed on the Internet. For example, the virality of the controversial Kony 2012 video, which sought to bring to justice the internationally wanted Ugandan war criminal Joseph Kony, was influenced strongly by sharing of the video amongst Facebook friends. Friends kept seeing the Kony video on their feed and decided to view it. Many then posted the video as a status update and changed their photo to a Kony 2012 banner.


Though Facebook has grown rapidly, there are also segments of backlash, ‘Facebook fatigue’, against the pervasiveness of Facebook as illustrated by movements such as the 2010 ‘Quit Facebook Day’. Survey research found that 23% of American teens pulled in 2013 found Facebook to be the most important social site to them, a figure down from 42% in 2012. Some fear that ‘Facebooking’ may be affecting the interaction of co-present individuals in that they may place priority on Facebooking the moment rather than ‘living’ in it. Facebook has also been criticized for the ease of its use in cyber-bullying and its circulation of controversial videos (including beheading videos).


But as Facebook’s techno-dog years pile on, there is a serious question here about the future of Facebook. Some think it is too big for its own good and is destined the way of defunct social networks like Myspace. For example, a recent article in Time by Sam Frizell (@Sam_Frizell) drew attention to a paper by Cannarella and Spechler which uses disease models to infer, “the future suggests that Facebook will undergo a rapid decline in the coming years, losing 80% of its peak user base between 2015 and 2017.”


Though Facebook’s user base could decline rapidly in the coming years, I find predicting social technology use by epidemiological models problematic. Though some may see Facebook use as akin to a disease, it is after all a communications technology. Mobile telephone and e-mail use continues to grow. And as we become more networked, our desire to interact on online social networks is more akin to e-mail adoption than disease models. I think the real question here is more an economic one. Myspace died out as Facebook aggressively took over its market share. Whether Facebook’s market share will erode after it turns 10 is better served by economic models which take into account complex market dynamics.


Though its future is uncertain, its last ten years have seen Facebook become part of the fabric of our daily social communication. Facebook has also been in the international spotlight and been important to various sociopolitical movements. For example, the ‘We Are All Khaled Said’ group was prominently used in the Arab spring in Egypt in 2011. Communications technologies evolve and adopt to our social needs. As society has become more mobile, we have moved from landlines to mobile telephones and e-mail. Also, technology can and does become replaced. My view is that if Facebook goes the way of Myspace, another online social network technology would fill the void as we live in a global networked society where we now expect to connect with friends, colleagues, world news, and family in integrated multimedia social networks like Facebook (and Myspace and Friendster before it). So if Facebook does die off in the next five years, its effects on social communication will be felt for many years to come.

A newer version of this article was published in The Conversation.