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Wednesday, July 13 • 13:46 - 15:15
One Day in the Life of a National Twittersphere

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Location: PSH (Professor Stuart Hall Building) - 314, 
Goldsmiths, University of London, Building 2
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  • Axel Bruns, Queensland University of Technology, Australia
  • Brenda Moon, Queensland University of Technology, Australia


Much of the existing research into the uses of social media platforms focusses on the exceptional: key moments in politics (e.g. Larsson & Moe, 2014; Sauter & Bruns, 2015, Papacharissi & Blasiola, 2016), sports (e.g. Blaszka et al., 2012; Highfield, 2014), brand management (e.g. Krüger et al., 2012; Nitins & Burgess, 2014), or crisis communication (e.g. Mendoza et al., 2010; Palen et al., 2010; Shaw et al., 2013). For the case of Twitter, because of the way that the Twitter API privileges certain data gathering approaches, such work is usually centred on one or more hashtags or keywords (Burgess & Bruns, 2015). This line of inquiry has produced many useful insights into the uses of Twitter – as documented for example in the collection Hashtag Publics (Rambukkana, 2015) – but arguably it covers only one subset of the various uses of the platform. Routine and everyday social media practices remain comparatively underexamined as a result; for Twitter, therefore, what results is an overrepresentation in the literature of the loudest voices – those users who contribute actively to popular hashtags.


This paper presents progress results from a major new study that examines user activity patterns on Twitter well beyond limited hashtag collections, drawing on a comprehensive dataset that tracks the public activities of all Twitter accounts identified by their profile information as Australian. Building on this cohort (currently containing some 2.8 million accounts), we have already mapped the follower/followee relationships within the Australian Twittersphere (Bruns et al., 2014) to identify the clustering patterns that influence – arguably more so than the use of hashtags – how information flows between users. We have also identified the thematic drivers of cluster formation in the network, and have mapped participation in specific Twitter conversations across these clusters.

The paper builds on this earlier work by exploring in depth the day-to-day patterns of activity within the Australian Twittersphere, for a selection of several 24-hour periods during 2015. This provides a unique new insight into how, across an entire national Twittersphere, conversations between users unfold through the day, and documents the extent to which such interactions are guided by existing follower relationships, hashtags, or other contextual markers. Inter alia, our analysis will show which parts of the network are consistently active across all periods, and which are triggered by the events of the day; which are more focussed on publishing new content (through original tweets), on interpersonal conversation (through @mentions), or on news dissemination (through retweets); and which are influential across the network, or remain largely within their own clusters. What is revealed through this work is a largely hidden side of Twitter away from the prominent hashtags.


Our comprehensive dataset of the public tweets by some 2.8 million identified Australian accounts enables filtering by the timestamps of tweets. We select several 24-hour periods across 2015 (averaging between 900,000 and 1 million tweets per day), to capture all tweets by Australian users during these days; we then extract from the tweet text any @mentions and retweets of other users, and generate a network map of their interactions to examine the processes of interpersonal engagement between these accounts. In doing so, we determine the properties of this network (and how they change through the course of the day), and examine the extent to which @mention or retweet engagement is a feature of overall activity in the Australian Twittersphere at any one point (that is, to what extent users are simply tweeting undirected personal statements, talk with each other through @mentions, or share other accounts’ posts through retweets). We also correlate this with the network clusters we have already identified in the follower network, to explore whether specific practices (posting, @mentioning, retweeting) are more prevalent in particular clusters of the network.


The outcomes from this study provide new insights into the dynamics of Twitter engagement well beyond well-understood phenomena such as hashtags. They shed new light on how everyday users utilise Twitter, and document the degree of diversity of the personal networks they actively engage with.

Future Work: 

We focus here in the first place on the documentation of comparatively ordinary days in the Australian Twittersphere. Future work will compare such patterns with extraordinary periods (such as major political, media, or sporting events), to explore how and to what extent the routine patterns of Twitter engagement change as breaking news disrupts users’ activities. Additionally, the network analysis presented here will also be combined with automated textual analysis, to examine whether changes in activity patterns through the day are correlated with thematic shifts in the content of the tweets.


Blaszka, M., Burch, L.M., Frederick, E.L., Clavio, G., & Walsh, P. (2012). #WorldSeries: An Empirical Examination of a Twitter Hashtag during a Major Sporting Event. International Journal of Sport Communication5(4): 435-453.

Bruns, A., Burgess, J., & Highfield, T. (2014). A “Big Data” Approach to Mapping the Australian Twittersphere. In P.L. Arthur & K. Bode (Eds.), Advancing Digital Humanities: Research, Methods, Theories (pp. 113–129). Houndmills: Palgrave Macmillan.

Burgess, J., & Bruns, A. (2015). Easy Data, Hard Data: The Politics and Pragmatics of Twitter Research after the Computational Turn. In G. Langlois, J. Redden, & G. Elmer (Eds.), Compromised Data: From Social Media to Big Data (pp. 93–111). New York: Bloomsbury Academic.

Highfield, T. (2014). Following the Yellow Jersey: Tweeting the Tour de France. In K. Weller et al., (Eds.), Twitter and Society (pp. 249-262). New York: Peter Lang.

Krüger, N., Stieglitz, S., & Potthoff, T. (2012). Brand Communication in Twitter: A Case Study on Adidas. In PACIS 2012 Proceedings (paper 161). Retrieved from http://aisel.aisnet.org/pacis2012/161.

Larsson, A.O., & Moe, H. (2014). Twitter in Politics and Elections: Insights from Scandinavia. In K. Weller et al., (Eds.), Twitter and Society (pp. 319-330). New York: Peter Lang.

Mendoza, M., Poblete, B., & Castillo, C. (2010). Twitter under Crisis: Can We Trust What We RT? In Proceedings of the First Workshop on Social Media Analytics (SOMA ’10) (pp. 71-79). Retrieved from http://snap.stanford.edu/soma2010/papers/soma2010_11.pdf.

Nitins, T., & Burgess, J. (2014). Twitter, Brands, and User Engagement. In K. Weller et al., (Eds.), Twitter and Society (pp. 293-303). New York: Peter Lang.

Palen, l., Starbird, K., Vieweg, S., & Hughes, A. (2010). Twitter-Based Information Distribution during the 2009 Red River Valley Flood Threat. Bulletin of the American Society for Information Science and Technology, 36(5): 13-17.

Rambukkana, N. (Ed.). (2015). Hashtag Publics: The Power and Politics of Discursive Networks. New York: Peter Lang.

Papacharissi, Z., & Blasiola, S. (2016). Structures of Feeling, Storytelling, and Social Media: The Case of #Egypt. In Bruns et al. (Eds.), The Routledge Companion to Social Media and Politics (pp. 211-222). London: Routledge.

Sauter, T., & Bruns, A. (2015). #auspol: The Hashtag as Community, Event, and Material Object for Engaging with Australian Politics. In N. Rambukkana (Ed.), Hashtag Publics: The Power and Politics of Discursive Networks (pp. 47–60). New York: Peter Lang.

Shaw, F., Burgess, J., Crawford, K., & Bruns, A. (2013). Sharing News, Making Sense, Saying Thanks: Patterns of Talk on Twitter during the Queensland Floods. Australian Journal of Communication, 40(1), 23-39. Retrieved from http://search.informit.com.au/documentSummary;dn=430834117446976;res=IELHSS.

Wednesday July 13, 2016 13:46 - 15:15 UTC
PSH (Professor Stuart Hall Building) - 314 Goldsmiths University, Building 2