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.

References:

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

The Facebook Psychology ‘experiment’ which manipulated the emotional content of nearly 700,000 users provides evidence that corporations need to have review procedures in terms of ethics that universities of been developing for some years surrounding social media research. In a university context, Institutional Review Boards (IRBs) are responsible for monitoring the ethics of any research conducted at the University. The US government’s Department of Health and Human Services publishes very detailed guidance for human subjects research. Section 2(a) of their IRB guidelines states that “for the IRB to approve research […] criteria include, among other things […] risks, potential benefits, informed consent, and safeguards for human subjects”. Most IRB’s take this mission quite seriously and err on the side of caution as people’s welfare is at stake.

The reason for this is simply to protect human subjects. Indeed, part of IRB reviews also evaluate whether particularly vulnerable populations (e.g. minors, people with mental/physical disabilities, women who are pregnant, and various other groups depending on context) are not additionally harmed due to research conducted. Animal research protocols follow similar logics. Before University researchers conduct social research, the ethical implications of the research are broadly evaluated within ethics and other criteria. If any human subject is participating in a social experiment or any social research, most studies either require signed informed consent or a similar protocol which informs participants of any risks associated with the research and allows them the option to opt out if they do not agree with the risks or any other parameters of the research.

Therefore, I was tremendously saddened to read the Proceedings of the National Academy of Sciences (PNAS) paper co-authored by Facebook data scientist Adam D. I. Kramer, Jamie E. Guillory of University of California, San Francisco and Jeffrey T. Hancock of Cornell University titled ‘Experimental evidence of massive-scale emotional contagion through social networks’. The authors of this study argue that agreement to Facebook’s ‘Data Use Policy’ constitutes informed consent (p. 8789). The paper uses a Big Data (or in their words ‘massive’) perspective to evaluate emotional behavior on Facebook (of 689,003 users). Specifically, the authors designed an experiment with a control and experimental group in which they manipulated the emotional sentiment of content in a selection of Facebook users’ feeds to omit positive and negative text content. Their conclusion was that the presence of positive emotion in feed content encouraged the user to post more positive emotional content. They also found that the presence of negative emotion in feed content encouraged the production of negative content (hence the disease metaphor of contagion). In my opinion, any potential scientific value of these findings (despite how valuable they may be) is outweighed by gross ethical negligence.

This experiment should have never gone ahead. Why? Because manipulating people’s emotional behavior ALWAYS involves risks. Or as Walden succinctly put it ‘Facebook intentionally made thousands upon thousands of people sad.’

In some cases, emotional interventions may be thought to be justifiable by participants. But, it is potential research subjects who should (via informed consent) make that decision. Without informed consent, a researcher is playing God. And the consequences are steep. In the case of the Facebook experiment, hundreds of thousands of users were subjected to negative content in their feeds. We do not know if suicidal users were part of the experimental group or individuals with severe depression, eating disorders, or conditions of self-harm. We will never know what harm this experiment did (which could have even lead to a spectrum of harm from low-level malaise to suicide). Some users had a higher percentage of positive/negative content omitted (between 10%-90% according to Kramer and his authors. Importantly, some users had up to 90% of positive content stripped out of their feeds, which is significant. And users stripped of negative content can argue social engineering.

To conduct a psychological experiment that is properly scientific, ethics needs to be central. And this is truly not the case here. Facebook and its academic co-authors have conducted bad science and give the field of data science a bad name. PNAS is a respected journal and anyone submitting should have complied with accepted ethical guidelines regardless of the fact that Facebook is not an academic institution. Additionally, two of the authors are at academic institutions and, as such, have professional ethical standards to adhere to. In the case of the lead author from Facebook, the company’s Data Use Policy has been used as a shockingly poor proxy for a full human subjects review with informed consent. What is particularly upsetting is that this was an experiment that probably did real harm. Some have argued that at least Facebook published their experiment while other companies are ultra-secretive. Rather than praising Facebook for this, such experiments cast light on the major ethical issues behind corporate research of our online data and our need to bring these debates into the public sphere.

A key domain in which Twitter is becoming important is in shaping the two-way relationship of television and social media. Specifically, live tweeting during television watching is shaping live media experiences in general. And, we are increasingly tweeting to the events of our lives (from news events to concerts). Twitter currently fills an important gap in social media which goes beyond information exchange to making entertainment and other events more socially experienced.

Dick Costolo has made clear that Twitter’s growth model is not focused on specific user growth targets, but rather is about building higher levels of engagement with the platform. What Twitter has is a global presence and household name recognition. But its problem is that perhaps the structure and form of the medium both put people off of joining or make it hard for them to be active. This has led to the trend of Twitter geeks who tweet often and don’t think twice about @-mentions. Your average person may just see the @ and shy away from a perceived wall of geek-based syntax. I think this last challenge is major, but one that is surmountable through creative, easy-to-use interfaces and other innovations and can lead to a new phase for Twitter and our engagements with it.

Television watching has always been a social process (e.g. a family gathering around the TV or colleagues at work talking about a show from the night before). However, the types of social interaction now possible with social media have changed how we watch TV. Specifically, new forms of ‘social TV viewing’ have produced conversations between TV watchers who are not geographically co-located and may or may not even be watching the TV show at the same time. This is a major change in the form and reach of the social side of TV watching.

Estimates have placed around 40% of evening tweets as television-related. Last year, Twitter Amplify, a TV ad targeting system was launched in the US. Twitter’s ad buy remains small in comparison to Facebook, but Amplify and similar products may provide new ways to market video advertising and, importantly, data analytics regarding engagement with a brand’s TV ads. The success of this is partially premised on the fact that users tweeting about a TV show are assumed to have watched the TV program the ad ran against. There are, of course, some limitations with this approach. However, an ad by Heineken during the US open men’s finals in September 2013 was promoted via Amplify and saw about 18,000 views, retweets, and comments. I think there is definitely potential for Twitter to better these relatively new products and further capitalize on social TV viewing, especially as it expands its social TV products outside of US markets.

Twitter’s social TV products like Amplify are still very young (Amplify was launched last year). Amplify is completely oriented to just the US market right now. However, social television watching has become a global trend. So, Twitter has totally new ad markets to tap into. Additionally, user engagement in terms of social TV watching is still very simple and organized around noisy hashtag-oriented engagement which is not always easy from a smart phone or tablet.

I think creative aggregation tools to distill the complex discourses emerging from social TV (and beyond) are completely lacking and Twitter has this and many other potential product avenues to not only spread its market reach, but greatly increase its user engagement (both of which affect revenue and profits). After all, Twitter is (currently) cash rich and could spend some real effort on helping users navigate through the sometimes tidal deluge that is a Twitter timeline.

I am not arguing that Twitter can or will deliver a mass audience on the scale of Facebook. Indeed, I think Twitter’s real promise is in distinction to Facebook in the sense of being a tool for public discourse rather than the more bounded friend networks of Facebook (which also have value of course). In my opinion, Twitter’s success is dependent on not deviating from its attractiveness to users, but creatively taking on user experience challenges.

I think our current experience of social television watching via Twitter is quite primitive. I think users want to spend more time on Twitter and further interact with not just television, but media content more generally. For example, I think people want a more immersive social TV experience which includes the ability to watch content within Twitter and tweet in reference to a particular scene (or even drawing a circle around a part of the frame) and this rich context is embedded within the tweet. Users want to engage at these more sophisticated levels and Twitter just doesn’t have the power to do this yet. In terms of ads, these much higher levels of detail could lead to much more relevant ad delivery (like pushing information about the Nike Air Jordan XX9 if an actor is wearing the shoe and it has been tagged in a tweet). More advanced machine-learning driven data backends could enrich this process even further.

Importantly, these features could also play a role in bettering Twitter’s role in global civil society and keep Twitter in the public limelight for years to come. Visual interfaces don’t just have utility for social TV watching but could be used in social activism and disaster recovery for example.

Parts of this article were published as part of a moderated debate in The Wall Street Journal.

I wanted to see how the strike actions are doing in terms of online Twitter activity. The data comes from all #fairpayinhe tweets from 6th – 10th February (which covers a one day and two hour strike). 2436 tweets make up the graph below:

fairpayinhe graphAnd here is some basic statistics on what is in the tweets:

Top URLs in Tweet in Entire Graph Entire Graph Count
http://www.unison.org.uk/news/higher-education-members-strike-for-fair-pay 68
http://fairpay.web.ucu.org.uk/2014/02/07/he-two-hour-strike-10-february-2014/ 37
http://union-news.co.uk/2014/02/dock-us-days-pay-two-hour-strike-well-strike-day/ 26
http://fairpay.web.ucu.org.uk/2014/02/04/a-new-briefing-on-the-he-dispute-for-students/#.Uvih0KYFG7A.twitter 22
http://fairpay.web.ucu.org.uk/2014/02/04/a-new-briefing-on-the-he-dispute-for-students/#.UviW3Yg9oCp.twitter 22
http://storify.com/ucu/what-is-a-university 19
http://fairpay.web.ucu.org.uk/2014/02/04/a-new-briefing-on-the-he-dispute-for-students/#.UviUC2ic1Mk.twitter 18
http://storify.com/counterfireorg/he-strike-6-feb-fairpayinhe?utm_content=storify-pingback&utm_source=direct-sfy.co&utm_medium=sfy.co-twitter&utm_campaign=&awesm=sfy.co_gbVm 18
http://fairpay.web.ucu.org.uk/2014/02/05/live-6-february-he-strike-action/ 17
http://www.fairpayinhe.org.uk/whos-signed/ 17

 

Top Hashtags in Tweet in Entire Graph Entire Graph Count
fairpayinHE 1811
fairpayinhe 208
tubestrike 146
ucu 101
UCU 97
FairPayinHE 70
FairPayInHE 61
solidarity 52
Unite 51
EIS 43

 

Top Words in Tweet in Entire Graph Entire Graph Count
rt 1860
fairpayinhe 1717
ucu 1042
strike 865
pay 439
today 322
picket 265
students 261
solidarity 246
more 244

 

Top @ Mentioned in Entire Graph Entire Graph Count
ucu 727
unisoninhe 154
unisontweets 147
[Anonymized for privacy] A writer 138
unitetheunion 85
ucuscotland 69
[Anonymized for privacy] A lecturer 43
[Anonymized for privacy] A socialist feminist 38
ucummoss 38
leedsucu 37

 

Top Hashtags in Tweet in Entire Graph Entire Graph Count
fairpayinHE 1811
fairpayinhe 208
tubestrike 146
ucu 101
UCU 97
FairPayinHE 70
FairPayInHE 61
solidarity 52
Unite 51
EIS 43

Though we increasingly understand what happens online is not any less ‘real’ than what happens offline, it can be easy for some to perceive that they are talking to a computer when they post on social media, rather than publishing within a space of public social communication. For example, there have been many cases on Twitter and Facebook where disgruntled employees post inappropriate messages about their bosses, which they would not have uttered offline. The logic here is that the act of typing on a keyboard can sometimes lead to a perception that what you type is somehow less ‘real’ or perhaps kind of trivial.

 

But, of course, it is no less real or trivial. Social media sites such as Twitter have been host to racialized talk about immigration or can respond to events in racialized ways (for example Charlene White’s refusal to wear a poppy). In terms of anti-racism, Twitter users often police the medium for ‘casual’ forms of racism. It is the latter that I have taken a particular interest in within my research of social media and Twitter specifically. So when Madonna used the N-word on January 17, 2014 via Instagram, my casual racist sensor went off. For those not familiar with this incident, Madonna Instagrammed a picture of her son Rocco Ritchie while boxing, adding the caption: “No one messes with Dirty Soap! Mama said knock you out! #disni**a”. Madonna’s million plus Instagram followers received the image, which nearly instantaneously circulated to Twitter and  its diverse audiences. Not only is the use of the N-word clearly inappropriate, but embedding it within a racial hashtag contributes to larger hashtag-based casual racist discourses on Twitter and other social media. Madonna’s Instagram photo caption reveals that she sees a certain normalcy of the N-word. More dangerously, her worldwide celebrity status, legitimizes racial hashtags through her casual use of the N-word on Instagram.

 

Though it is important to make larger arguments about how the Madonna incident is a case of casual racism which has major implications, I think it is also important to understand the micro-level interactions on social media which Madonna prompted. To do this, I first collected all tweets with the #disni**a hashtag and then did the same for all tweets containing ‘Madonna’. The latter had very little to add in terms of data that was not already encompassed by the former. As #disni**a was a more inclusive search term, I created a graph of this network.

#disni__a network graph

[squares represent users with more than 1,000 followers and the size of the user icons is scaled by the number of RTs or @mentions].

 

The noticeable black square (between the blue and purple squares) represents Madonna (rather than her tweeting out, people are tweeting at her). The blue square represents an East Asian-American actor/comedian on MTV (@Traphik ; 420,000 followers) who tweeted “Lol Madonna hashtagged a pic with #disnigga!? Do u kids see what uve done! It’s like grandpa saying “yo homie G” cuz it’s all he hears!”. The purple square represents a black female blogger (@luvvie) with over 27,000 followers who had two tweets heavily retweeted, “Madonna talmbout she called her son #DisNigga as term of endearment. I wanna lock her in a stadium of seats so she can pick plenty to have” and “If Madonna is calling her white son #DisNigga, what is she calling her little Malawian son? I’m unable to deal.” It is interesting that the two centers of the tweet network for #disni**a are not white and both use humor to interrogate Madonna’s Instagram incident. From a social graph perspective, they steered the conversation on Twitter.

 

Madonna’s racist outburst was clearly racist and was covered in the popular press as such. The ‘thought leaders’ on Twitter around the #disni**a hashtag, however, saw this as an opportunity to both ridicule Madonna (e.g. PTraphik labeling Madonna as an out of touch Grandma), but also reflect on her use of the racial slur. Madonna made clear that she did not intend the comment as ‘a racial slur’ and that she is ‘not a racist’. However, this incident highlights the extreme prevalence of racialized language on social media, when even a self-purported liberal celebrity who pushed gender boundaries in the 80s/90s uses a racialized hashtag. I think this incident makes clear that we should not be lulled into a false sense of security of de-racialized virtual spaces, but that the virtual can also give us glimpses into peoples’ backstage lives, which we would not usually have access to offline. Ultimately, the Material Girl has been shamed on Twitter. It would have been nice to see more of a critical engaged discourse on Twitter about the incident, but that is not how social media usually operates.

A version of this blog has been published by The Runnymede Trust on their Race Card blog.

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.