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Social Media Network Mapping

Mapping Online Publics on Twitter (DIATA11)

Düsseldorf Workshop on Interdisciplinary Approaches to Twitter Analysis (DIATA2011)

Mapping Online Publics on Twitter

Axel Bruns, Jean Burgess, and Stephen Harrington

  • 14 September 2011 – DIATA11 workshop, Düsseldorf

The Use of Twitter Hashtags in the Formation of Ad Hoc Publics (ECPR 2011)

European Consortium for Political Research (ECPR 2011)

The Use of Twitter Hashtags in the Formation of Ad Hoc Publics

Axel Bruns and Jean Burgess

As the use of Twitter has become more commonplace throughout many nations, its role in political discussion has also increased. This has been evident in contexts ranging from general political discussion through local, state, and national elections (such as in the 2010 Australian elections) to protests and other activist mobilisation (for example in the current uprisings in Tunisia, Egypt, and Yemen, as well as in the controversy around WikiLeaks).

Research into the use of Twitter in such political contexts has also developed rapidly, aided by substantial advancements in quantitative and qualitative methodologies for capturing, processing, analysing, and visualising Twitter updates by large groups of users. Recent work has especially highlighted the role of the Twitter hashtag – a short keyword, prefixed with the hash symbol ‘#’ – as a means of coordinating a distributed discussion between more or less large groups of users, who do not need to be connected through existing ‘follower’ networks.

Twitter hashtags – such as ‘#ausvotes’ for the 2010 Australian elections, ‘#londonriots’ for the coordination of information and political debates around the recent unrest in London, or ‘#wikileaks’ for the controversy around WikiLeaks thus aid the formation of ad hoc publics around specific themes and topics. They emerge from within the Twitter community – sometimes as a result of pre-planning or quickly reached consensus, sometimes through protracted debate about what the appropriate hashtag for an event or topic should be (which may also lead to the formation of competing publics using different hashtags).

Drawing on innovative methodologies for the study of Twitter content, this paper examines the use of hashtags in political debate in the context of a number of major case studies.

Making Sense of Twitter Hashtags as Ad Hoc Publics

Our paper was next at ECPR 2011 – and we presented our thoughts on the role of Twitter hashtags in providing a space for ad hoc online publics. This also builds on some of the work we’ve done during our week-long workshop at the University of Münster last week. I’ll add audio shortly Audio included below, PDF available here:

Towards Semantic Polling?

Reykjavík.
The next speaker at ECPR 2011 is Ben O’Loughlin, whose interest is in the effect of near real-time semantic analysis of public sentiments (online) on continuing political processes: in the end, we may end up with a kind of semantic polling of available social media and other electronic data, which enables political actors to target their messages to voters with unprecedented precision and speed. The 2010 election in the U.K. may have been the first rudimentary example of such a feedback loop.

Ben’s study examined the social media data used by TV and print journalists during the election, and interviewed key actors about their emerging practices in dealing with such data. Three main types of reporting were notable: anecdotal (pulling random tweets out of the timeline); quantitative (general stats on user activity as reported by various polling companies); and semantic (processing the content of social media sources).

Identifying Events from Twitter Bursts

Reykjavík.
The next speaker at ECPR 2011 is Andreas Jungherr, whose interest is in using Twitter data to detect events by identifying sudden bursts of activity in the continuing stream of updates. Such research is especially straightforward on Twitter, due to its convenient API access formats; additionally, the short format of Twitter messages means that key themes in messages can be more easily identified.

Twitter itself does some of this, of course, with its ‘trending topics’ (also broken down for specific geographical regions); further, it is possible to identify the links which are shared as part of tweets, of course, as well as identifying hashtags, @replies, and retweets. And tweets are exactly timestamped, allowing for close analysis of temppral developments.

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