Helen Webb starts off the next session of Social Media and Society, and begins by suggesting that social media have a transformative capacity for social research as well. To begin with, social media research challenges established conceptual and methodological approaches: they enable us to explore and revise existing theories of social interaction and self-presentation, for instance; or to review patterns and sequences of interaction in order to develop new views on conversational processes.
It's the final day at Social Media and Society, and today's keynote is by Helen Kennedy. She's beginning with the question of how data make us feel: and it is a question that reflects the power of data, of metrics, in an environment where such data have become ordinary and everyday. As data mining becomes more commonplace, new data relations emerge, and these are increasingly characterised by emotion as much as by rationality. This represents a desire for numbers, and points to some of the contradictions that include a hunger for as well as a criticism of numbers. How we get through the visualisation of numbers also plays an important role.
Social media data form part of a larger ecosystem of connective data in this context. Social media data mining has also become ordinary – and should such ordinary forms of social media data mining concern us in the same way that more exceptional data (such as the Snowden leaks) should concern us? Helen has examined this in close engagement with social media data generators and users, and this has also uncovered the visceral reactions that people have when they encounter a data visualisation. Such responses to 'seeing data' also deserve further research: how do we live with data from the bottom up?
Next up at Social Media and Society is Jacob Groshek, whose interest is in new modes of journalism on social media. Journalism has traditionally been operating through gatekeeping, deciding what news is being published to their audiences and what news do not. This is still a key mechanism in digital networks, but increasingly redesigned to adjust to the multitude of senders and receivers that are now present in online spaces. All of us are now potential gatekeepers, making our own decisions about what to publish and what to ignore.
OK, so I'm afraid I missed the first paper by Ching-ya Lin in this Social Media and Society session on journalism and propaganda because I was talking to one of the poster presenters. The second speaker is Ebru Kayaalp, who takes an actor-network theory approach to the study of the propaganda wars between the U.S. and ISIS.
The final speaker in this Social Media and Society session is Moses Boudourides, who presents a study of the affective publics on Twitter surrounding the European refugee crisis and the Paris terrorist attacks. The project tracked some twenty keywords and hashtags relating to the refugee crisis, capturing a substantial volume of tweets that were further processed using Python.
The third speaker in this Social Media and Society session is Alexia Maddox, whose interest is in the study of online discussions of illicit drug use. Illicit drugs are a stigmatised topic, which has pushed discussion into more permissive spaces such as social media. In Australia, there has been a renewed push to legalise medicinal marijuana, which has increased the volume of discussions about the drug, and this provides the current context for this study.
The next speaker at Social Media and Society is Christopher Mascaro, whose interest is in 'big data' on political communication online. Political discourse studies have traditionally been restrained by geographic and social access, and 'big data' from online activities can overcome some of these barriers; it also introduces some new limitations that must be considered, however.
The next session at Social Media and Society is on 'big data', and begins with Andra Siibak (who is also the programme chair for AoIR 2017 in Tartu, Estonia!). She highlights the possible methodological shifts that arise from the use of 'big data' in social science research: this is in part seen as a shift towards more quantitative methods, but also as a more nuanced and methodological shift from designed to more 'organic' data, whatever we may mean by this. Approaches that are built on formulating and testing preconceived hypotheses may also be challenged by other, alternative approaches.
It's the second day of Social Media and Society in London, and after a day of workshops we're now starting the conference proper with a keynote by Susan Halford. She begins by pointing out the significant impact of social media on a wide range of areas of public and everyday life. We're constantly presented with the digital traces of social media – with social media data at an unprecedented scale, telling us something about what people do with social media in their everyday lives. This is an unexpected gift, but is also causing significant concern and scepticism.
What is the quality of the data – what are they, what do they represent, what claims can be made from these data? Some social scientists are even suggesting that such data are dangerous and can affect the public reputation of the scientists and disciplines using them. Few people were experts in working with social media data when these data first arrived – we are building the boat as we row it, to use an old Norwegian saying, and we're learning about how to do so as we go along.
I’m delighted to share a couple of new publications written with my esteemed colleagues in the QUT Digital Media Research Centre – and as if we weren’t working on enough research projects already, this year is about to get an awful lot busier soon, too. First, though, to the latest articles:
This article, in a great special issue of Communication Research and Practice on digital media research methods that was edited by my former PhD student Jonathon Hutchinson, updates my previous work with Stefan Stieglitz that explored some key metrics for a broad range of hashtag datasets and identified some possible types of hashtags using those metrics. In this new work, we find that the patterns we documented then still hold today, and add some further pointers towards other types of hashtags. We’re particularly thankful to our colleagues Jan Schmidt, Fabio Giglietto, Steven McDermott, Till Keyling, Xi Cui, Steffen Lemke, Isabella Peters, Athanasios Mazarakis, Yu-Chung Cheng, and Pailin Chen, who contributed some of their own datasets to our analysis.