One more post before I head home from the AoIR 2015 conference in Phoenix: during the conference, I also received my author’s copy of Hashtag Publics, an excellent new collection edited by Nathan Rambukkana. In this collection, Jean Burgess and I published an updated version of our paper from the ECPR conference in Reykjavík, which conceptualises (some) hashtag communities as ad hoc publics – and Theresa Sauter and I also have a chapter in the book that explores the #auspol hashtag for Australian politics.
Finally in this AoIR 2015 session, we move on to Greg Elmer, one of the editors of Compromised Data: From Social Media to Big Data. His contribution is focussed on the practice of collecting data from social media sites, some of which is done using some very simple Web scraping tools (as Edward Snowden did at the NSA, apparently).
Scraping is now a common practice in a number of contexts; some sites scrape from mainstream news sites in order to gain better search rankings, for example. Google briefly introduced a tool to identify where site content had been scraped …
The next speaker in the Compromised Data session at AoIR 2015 is Robert Gehl, whose focus is on the effects of corporate social media. There is a conflict between the critiques of proprietary social media spaces and the obvious pleasures of using social media; what do we do about this?
Robert suggests that we make our own, by building alternatives to the standard commercial social media platforms. This proceeds by critical reverse engineering: taking apart existing artefacts to produce new and alternative artefacts that bear a relation to the old while striving towards justice.
My QUT DMRC colleague Jean Burgess and I are next at AoIR 2015, presenting the core points from our chapter "Easy Data, Hard Data" in the Compromised Data collection. (The slides are below.) The chapter thinks through the pragmatics and politics of being social media researchers in a complex and precarious environment, and thus builds on David Berry's work on the computational turn in humanities and social science research.
This turn towards large data is instrumental as well as transformational – it has exciting practical dimensions as new but unevenly distributed and challenging research opportunities arise, but …
The next speaker at AoIR 2015 is Joanna Redden, another contributor to the Compromised Data: From Social Media to Big Data collection. She focusses especially on how data are being used by governments, and how this impacts particularly on issues of poverty and inequality. Her work is based on interviews with public servants and consultants in Canada, and builds a picture of how and where data are being used in the government.
Data here include government-owned and -created data, as well as from other sources and services including social media. How can we unblackbox and make transparent these uses and …
The final panel at AoIR 2015 for today is the Compromised Data panel, celebrating the release of the book of the same name. Ganaele Langlois starts us off by highlighting the key themes of the book: data are now crucial to building the social, and the gaps and omissions in the data therefore have very significant impacts.
Governments such as the Harper government in Canada, which has just been removed from office, seek to hide some forms of data because it is politically expedient to do so, and so data are political; data are also shaped by the sources we …
The final speaker in this session at AoIR 2015 is Helen Kennedy, whose interest is in how people interact with data visualisations. This is very important in the context of the current datafication trend. But existing literature in this field lacks a user-centred knowledge base – much is driven by designers' instincts of what constitutes a good data visualisation. It mobilises narrow definitions and measures of effectiveness and provides little information about participants, while ignoring social and cultural factors.
This work, then, could learn from media and cultural studies work that investigates how audiences engage with media texts. Helen's work …
The second speaker on this AoIR 2015 session is QUT DMRC PhD researcher Jing Zeng, whose focus is on the challenges associated with accessing data from popular Chinese social media platform Weibo. Weibo, meaning 'micro-blog' in Chinese, is a Chinese take on social media services such as Twitter. Sina Weibo is now the most successful of such services in China, with several hundred million users now present on the site.
There is a substantial volume of research now addressing Weibo, but inside of China much of this work still comes only from computer science fields, while …
The final presenter at AoIR 2015 today is Anissa Tanweer, whose interest is in the shift towards big data. This has been a major buzzword, and has enabled the rise of data science; her team has conducted an ethnography of the data science environment.
One of the major challenges in working with big data is how researchers envision their data; it is no longer possible to visually review the entire dataset, for example, and the picture of the dataset is constantly evolving. This is especially crucial in moments of breakdown that require a repair of the dataset, and may lead …
The next session at AoIR 2015 is starting with Catherine Brooks, whose interest is in scientific collaboration: how do scientists organise themselves and manage their data? This is an increasingly crucial question in (big) data-enabled science. One problem is that of dark data – unused, overlooked, rejected data from past research projects, which could be placed on cloud-based storage platforms to make them useful again.
These questions could be understood from actor-network theory or human and technology studies perspectives – the ultimate goal could be the democratisation of data, to increase their further usefulness. Data often follow the paths of …
. His contribution is focussed on the practice of collecting data from social media sites, some of which is done using some very simple Web scraping tools (as Edward Snowden did at the NSA, apparently). 
