Researching with Twitter timeline data: A demonstration via “everyday” socio-political talk around welfare provision

Phillip Brooker, Julie Barnett, John Vines, Shaun Lawson, Tom Feltwell, Kiel Long, Gavin Wood

Research output: Contribution to journalArticlepeer-review

7 Citations (SciVal)


Increasingly, social media platforms are understood by researchers to be valuable sites of politically-relevant discussions. However, analyses of social media data are typically undertaken by focusing on ‘snapshots’ of issues using query-keyword search strategies. This paper develops an alternative, less issue-based, mode of analysing Twitter data. It provides a framework for working qualitatively with longitudinally-oriented Twitter data (user-timelines), and uses an empirical case to consider the value and the challenges of doing so. Exploring how Twitter users place “everyday” talk around the socio-political issue of UK welfare provision, we draw on digital ethnography and narrative analysis techniques to analyse 25 user-timelines and identify three distinctions in users’ practices: users’ engagements with welfare as TV entertainment or as a socio-political concern; the degree of sustained engagement with said issues, and; the degree to which users’ tweeting practices around welfare were congruent with or in contrast to their other tweets. With this analytic orientation, we demonstrate how a longitudinal analysis of user-timelines provides rich resources that facilitate a more nuanced understanding of user engagement in everyday socio-political discussions online.

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalBig Data and Society
Issue number1
Early online date3 Apr 2018
Publication statusPublished - 2018


  • digital ethnography
  • digital methods
  • narrative analysis
  • Social media analytics
  • social welfare
  • socio-political issues

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Information Systems and Management
  • Communication
  • Library and Information Sciences


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