社会化媒体
操作化
概念化
微博
政治
社会学
背景(考古学)
独创性
公共关系
价值(数学)
数据科学
政治沟通
电子参与
计算机科学
政治学
社会科学
万维网
认识论
人工智能
古生物学
定性研究
法学
哲学
机器学习
生物
作者
Vidushi Pandey,Sumeet Gupta,Manojit Chattopadhyay
出处
期刊:Information Technology & People
[Emerald (MCB UP)]
日期:2019-10-18
卷期号:33 (4): 1053-1075
被引量:5
标识
DOI:10.1108/itp-03-2018-0140
摘要
Purpose The purpose of this paper is to explore how the use of social media by citizens has impacted the traditional conceptualization and operationalization of political participation in the society. Design/methodology/approach This study is based on Teorell et al. ’s (2007) classification of political participation which is modified to suit the current context of social media. The authors classified 15,460 tweets along three parameters suggested in the framework with help of supervised text classification algorithms. Findings The analysis reveals that Activism is the most prominent form of political participation undertaken by people on Twitter. Other activities that were undertaken include Formal Political participation and Consumer participation. The analysis also reveals that identity of participant does not play a classifying role as expected from the theoretical framework. It was found that the social media as a platform facilitates new forms of participation which are not feasible offline. Research limitations/implications The current work considers only the microblogging platform of Twitter as the data source. For a more comprehensive insight, analysis of other social media platforms is also required. Originality/value To the best of the authors’ knowledge, this is one of the few analyses where such a large database covering multiple social media events has been created and analysed using supervised text classification algorithms. A large proportion of previous studies on social media have been based on case study and have limited analysis to only a particular event on social media. Although there exist a few works that have studied a vast and varied collection of social media data (Gaby and Caren, 2012; Shirazi, 2013; Rane and Salem, 2012), such efforts are few in number. This study aims to add to that stream of work where a wider and more generalized set of social media data is studied.
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