'Big Data'

The last paper in this AoIR 2018 session was mine, presenting on our TrISMA project to gather social media data in Australia at scale. Here are the slides:

The third speaker in this AoIR 2018 session is Harsh Taneja, who promises to present an alternative history of big data. At present, many big data datasets are highly platform-specific, such data can generally be accessed via platform APIs or scraped from platform Websites. But big data research existed before the Internet: Harsh points here to the early days of advertising-supported broadcasting, when advertisers first required audience measurements.

The next speaker in our AoIR 2018 session is Ericka Menchen-Trevino, whose research interest is on the study of selective exposure; this is often studied through surveys or lab experiments, but can be usefully complemented with Web history data. Such an integration between conventional social science data and digital trace data provides a blueprint for new possibilities across a range of research interests, in fact.

I’ve spent the morning in an AoIR Executive meeting, but I’m back for the second session on this Friday morning at AoIR 2018 – and I also have a paper in this session. First off is Rasmus Helles, though, who presents the People’s Internet Project: a major global study, supported by the Carlsberg Foundation, that seeks to map out global variations in Internet development.

The next speaker in this AoIR 2018 session is Megan Boler, who continues our focus on algorithms. She begins by noting a concern about the affective politics of information warfare, as well as about the increasing targetting of emotions through social media activity.

Well, we’re finally here: AoIR 2018 in Montréal has begun. We start with the keynote by Jason Lewis, who addresses the continuing rise of white supremacy in recent years. He begins by referencing the novel Riding the Trail of Tears, which discusses a retracing of the removal of the Cherokee from their traditional lands through virtual technology, and the possibility of Indigeneity in a digital earth.

But such a perspective clashes with white supremacy, which is well established in societal power structures even without further action to entrench it more deeply. Jason compares this with the multi-layer hardware and software stack that digital interfaces operate on; we are subject to the regimes that the stack places upon us and have no meaningful way to escape them. In much the same way, white biases are a feature, not a bug of contemporary society at every level; in software, biases beget biases because new data and new systems are built on old data and old systems, and perpetuate their built-in assumptions, and the same is true in societal protocols. This is a millennia-long process or epistemological inertia.

The next speaker at Social Media & Society 2018 is Aske Kammer. He begins by noting that there is a resource exchange between media organisations and third party platforms like Facebook and Twitter. By embedding social media sharing tools or topical advertisements on their own pages, media organisations provide a window for third-party data capture in exchange for the platforms’ services.

The next presentation in this ICA 2018 session is by Drew Margolin, who highlights the growing use of computational methods in communication, and therefore the need to further scrutinise the methods that are popular here. Truth is revealed and reviewed through a succession of studies.

The next speaker at ICA 2018 is Theo Araujo, whose focus is especially on analysing image content from social media. There are a number of API solutions now becoming available for the analysis of such images, including from Google and Microsoft. The project tested such image analysis tools in the context of the visual self-representation of companies discussing their corporate social responsibility.

The next speaker in this ICA 2018 session is Fabian Pfaffenberger, who also highlights the unreliability of Twitter data. The API’s 1% sample is extremely biased, and the search API is also unreliable in what it delivers; historical data is especially incomplete as the search API delivers only tweets posted in the past 6-7 days and will not include deleted tweets or tweets from subsequently deleted or suspended accounts.