Finally for this session at Web Science 2016 we move to Sebastian Stommel, who begins by considering what we mean by Web science in the first place. He suggests that 'big data' serve as a macroscope: a new way of looking at things at scale, and an opportunity to create generative models to explain digital traces.

The second session on this final day of AoIR 2015 starts with Camille Yale, whose focus is on Netflix. Netflix represents a rearticulation of the commercial media system, rather than a revolution: it has an intense commodity orientation, global ambitions, and oligopolistic practices; it claims for itself that it is democratising entertainment, however.

The post-lunch session at AoIR 2015 is a panel on social media and elections that my colleague Tim Highfield and I are contributing to, but we begin with the excellent Anders Olof Larsson, whose focus is on recent Swedish elections. Sweden traditionally has a high level of election participation and substantial Internet and social media access, and social media have become increasingly visible in election campaigns, unsurprisingly this has increased over time.

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.

The next speaker in this AoIR 2015 session is Michael Humphrey, whose interest is in life stories in digital spaces. Today's talk is focussed on the idea of white privilege, however: this can also be understood through the language we use, which colours how we see the world around us. We look at life through many filters, and tell our story through these filters; some of us take an agentic approach to telling our stories (we are at the centre), while others take a more communal approach (we are part of a group).

The next speaker at ECREA 2014 is Stefania Milan, who begins by noting the social media response to the 2010 Haiti earthquake, using Ushahidi Maps as a key tool for mapping the local situation. This is a positive example of how civil society can put big data to good use: what forms of massive data collection are possible here, and how can they be used for good?

There has been an industrial revolution of data, but citizens face a paradox, as moral codes are not yet aligned with social practices. Big data may mean big control, but also more opportunities; we need data activism to mobilise a critical stance towards massive data collection, emerging perhaps from hacker movements but also involving ordinary users, and enabled but also constrained by software capabilities.

I'm spending the next couple of days in Sydney at the Australia-New Zealand Workshop on Campaign Management and Political Marketing, where I'm presenting a paper on the use of Twitter during the 2013 Australian federal election tomorrow. But we start today with an introduction by John Keane, who is reflecting on the history of elections during the post-war period.

He suggests that there are a number of big trends in this period. First, the electoral revolution: a huge increase in the number of countries which practice elections. Second, even despotic regimes use elections to legitimise themselves. Third, elections have been indigenised: the electoral process is being adjusted to take into account local traditions, from feeding the poor to driving away evil spirits.

The final panel at Digital Methods in Vienna is on Web monitoring, and starts with a paper by Jakob Jünger on Facepager, a tool for gathering data from Facebook. Such data could be scraped directly from the Web pages, or retrieved through the API; Facepager takes the second route, which has specific implications for the kind of data which are available for it.

For example, popular Facebook pages show a general estimate of how many likes they've received (e.g. "700k"), while the API returns an exact number; this needs to be considered in any analysis which examines the actual user experience, of course.