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

被引:7
|
作者
Brooker, Phillip [1 ]
Barnett, Julie [2 ]
Vines, John [3 ]
Lawson, Shaun [3 ]
Feltwell, Tom [3 ]
Long, Kiel [3 ]
Wood, Gavin [3 ]
机构
[1] Univ Liverpool, Room 1-53,Eleanor Rathbone Bldg,Bedford St South, Liverpool L69 7ZA, Merseyside, England
[2] Univ Bath, Bath, Avon, England
[3] Northumbria Univ, Newcastle Upon Tyne, Tyne & Wear, England
来源
BIG DATA & SOCIETY | 2018年 / 5卷 / 01期
基金
英国经济与社会研究理事会; 英国工程与自然科学研究理事会;
关键词
Social media analytics; digital methods; digital ethnography; narrative analysis; socio-political issues; social welfare; SOCIAL MEDIA; YOUTUBE; ENGLISH;
D O I
10.1177/2053951718766624
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
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.
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页数:13
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