How long is a tweet? Mapping dynamic conversation networks on Twitter using Gawk and Gephi
Bruns, Axel (2012) How long is a tweet? Mapping dynamic conversation networks on Twitter using Gawk and Gephi. Information, Communication & Society, 15(9), pp. 1323-1351.
Twitter is now well established as the world’s second most important social media platform, after Facebook. Its 140-character updates are designed for brief messaging, and its network structures are kept relatively flat and simple: messages from users are either public and visible to all (even to unregistered visitors using the Twitter website), or private and visible only to approved ‘followers’ of the sender; there are no more complex definitions of degrees of connection (family, friends, friends of friends) as they are available in other social networks. Over time, Twitter users have developed simple, but effective mechanisms for working around these limitations: ‘#hashtags’, which enable the manual or automatic collation of all tweets containing the same #hashtag, as well allowing users to subscribe to content feeds that contain only those tweets which feature specific #hashtags; and ‘@replies’, which allow senders to direct public messages even to users whom they do not already follow. This paper documents a methodology for extracting public Twitter activity data around specific #hashtags, and for processing these data in order to analyse and visualize the @reply networks existing between participating users – both overall, as a static network, and over time, to highlight the dynamic structure of @reply conversations. Such visualizations enable us to highlight the shifting roles played by individual participants, as well as the response of the overall #hashtag community to new stimuli – such as the entry of new participants or the availability of new information. Over longer timeframes, it is also possible to identify different phases in the overall discussion, or the formation of distinct clusters of preferentially interacting participants.
Impact and interest:
Citation counts are sourced monthly from and citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
|Item Type:||Journal Article|
|Additional Information:||Taylor and Francis iFirst publication.|
|Keywords:||web 2.0, social networking, research methodology, media studies, communications studies, computer-mediated communciation|
|ISSN:||1468-4462 (online) 1369-118X (print)|
|Subjects:||Australian and New Zealand Standard Research Classification > LANGUAGES COMMUNICATION AND CULTURE (200000) > COMMUNICATION AND MEDIA STUDIES (200100) > Communication Technology and Digital Media Studies (200102)|
|Divisions:||Current > Research Centres > ARC Centre of Excellence for Creative Industries and Innovation
Current > QUT Faculties and Divisions > Creative Industries Faculty
Past > Institutes > Institute for Creative Industries and Innovation
Current > Schools > Journalism, Media & Communication
|Copyright Owner:||Copyright 2011 Taylor and Francis|
|Copyright Statement:||This article may be used for research, teaching, and study purposed. any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden.|
|Deposited On:||04 Jun 2012 22:38|
|Last Modified:||17 Jun 2015 08:18|
Repository Staff Only: item control page