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Conference Round-up: Association of Internet Researchers: Networked Publics, 18-21 October 2017, University of Tartu, Estonia

08 November 2017 - BY Silvana di Gregorio

The Association of Internet Researchers is a cross-disciplinary academic association dedicated to Internet Studies. The association is international in scope and transcends traditional academic boundaries. Their annual conference has a highly selective process for papers which ensures that the quality is very high. There is a real mix of social scientists, digital humanities scholars as well as computer scientists. The Internet as a topic of study is in constant flux – with new platforms suddenly appearing, others declining and topics such as ‘fake news’ coming out of seemingly nowhere. This is the place to look for innovations in qualitative and mixed methods research.

Fig 1. Word Cloud of the conference abstracts

I have been following this group for a few years. I first became aware of them when I was looking for ethical guidelines in researching the Internet. They wrote their first framework in 2002, updated it in 2012 and there is a current working group to update the framework to take account of the continual evolution of the Internet and its use. If you are considering conducting research on the Internet you may want to start with their one page guide based on the 2012 guidelines.

Pre-conference workshops

As this was the first time I attended this conference, I wanted to get a sense of the range of research covered in the conference. I signed up for a pre-conference workshop on Digital Methods in Internet Research.  It covered using Tableau to analyse large Twitter datasets (with Axel Bruns), a walk-through method for studying apps (with Stefanie Duguay), understanding YouTube’s ranking algorithms (with Ariadna Matamoros-Fernandez), and recommendations for protecting your Internet identity and data (with Brenda Moon). All these presenters come from the Digital Media Research Centre at Queensland University of Technology. I learned a lot but I wished I could have split myself in half because at the same time was another workshop on analysing visual social media.

Keynote plenary

Professor Andrew Chadwick of the Centre of Communication and Culture at Loughborough University, UK gave an outstanding plenary on an analysis of Donald Trump’s social media strategy during the 2016 US Presidential election. The video is well worth watching, you can view it here. His talk begins at 28:32 minutes into the video.

Fig. 2 Tweet with link to Andrew Chadwick’s plenary video

There followed three full days of conference papers.  I cannot give justice to the range of papers that I heard but below are a few highlights from the conference relevant to qualitative and mixed methods research.

The analysis of visual data

Unsurprisingly visual data and its analysis play a big part in Internet research. I identified a few clusters of researchers engaged in this work. There are a number of researchers working with Annette Markham at Aarhus University, Denmark. Professor Markham teaches Masters students auto-ethnography and phenomenology through a six week course where they do a deep dive into their own digital experience. Since 2012 over 1000 students have created multi-media ethnographic narratives in this way. Gabriel Pereira was one of those students and illustrated how he recorded his own Internet use through video. He showed how video-editing is a qualitative method. He interspersed the videos of himself using social media with screenshots and videos of places where he was viewing social media.

Katrin Tiidenberg a post-doctoral researcher at Aarhus University, also discussed how she teaches Masters students to become ethnographers by looking at their behaviours using Instagram and Snapchat. They used video and audio recording, screenshots, written journal entries, field-notes and reflexive narrative accounts. These are just two examples of qualitative work coming out of Aarhus University and a wider network called Future Making , check out the link.

Fig. 3 Slide from Katrin Tiidenberg’s paper on students’ use of Instagram and Snapchat

On another tack, Helen Kennedy, Professor of Digital Society, Sheffield University, UK is concerned about what the public make of the visualizations of ‘big data’. Her experience of working with local government revealed that there was great enthusiasm for data represented in graphic charts. However, the desire for numbers was so strong that it did not matter whether the numbers were accurate or not. A campaign’s success is based on large numbers – they were not interested in discussions on limitations. She also pointed out that people have emotional responses to visualizations of ‘big data’ and more work needs to be done to understand such responses.

Fig. 4 2011 Census Map from ONS – an example of big data visualization

Check out this link for projects by Professor Kennedy, her students and other academics on the analysis of data visualizations - Seeing Data project -


Understanding how platforms use algorithms may not seem an obvious area for qualitative or even mixed methods research. However, I was intrigued by James Allen-Robertson’s use of Python and NVivo to understand Uber’s use of algorithms to manage their drivers. I should say that his paper was proceeded by an excellent theoretical framework by Alessandro Gandini of King’s College London for understanding labour relations in such ‘platform’ workspaces.

This framework synched nicely with Allen-Robertson’s study of analysing Uber drivers’ forum discussion group trying to make sense of the algorithms Uber uses to manage them.  Allen-Robertson used Python to topic model the discussions and then imported key topic areas in NVivo for in-depth analysis of the topics.  Uber drivers used the forum to discuss how the algorithms responded to certain behaviours and what they can do to influence the system.

Fig. 5 - Ways of analysing the gig economy – when your boss is an algorithm
I already mentioned Ariadna Matamoros-Fernandez’s pre-conference workshop on Understanding YouTube’s ranking algorithms. This is another example of a mixed methods approach to understanding algorithms. In the accompanying paper, she and her colleagues discuss moving from looking at ‘ranking algorithms’ to ‘ranking cultures’. She and her colleagues describe their approach as “situating the study of an ‘algorithm’ in the specific setting of the YouTube platform and its use cultures”. They use the visualizations generated by quantitative data on rankings over time as the starting point to look qualitatively at the particular videos, channels and events surrounding them.

Rieder, Bernhard, Matamoros-Fernandez, Ariadna, & Coromina, Oscar (2018) From ranking algorithms to ranking cultures: Investigating the modulations of visibility in YouTube search results, in Convergence, vol 24. No. 1 (February 2018)

Looking forward to next year

It is hard to summarise the wealth of knowledge generated by this conference – that is not to mention the enthusiasm and energy from the young researchers working in a cross-discipline and multi-method way.  I can hardly wait for next year’s conference which will be in Montreal on the 10-13 October 2018. I highly recommend it.