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Influence in Social Media: An Investigation of Tweets Spanning the 2011 Egyptian Revolution
MIS Quarterly ( IF 7.0 ) Pub Date : 2021-10-14 , DOI: 10.25300/misq/2021/15297
Srikanth Venkatesan , , Rohit Valecha , Niam Yaraghi , Onook Oh , H. Raghav Rao , , , ,

Through the lens of social movement theory, this paper investigates the drivers of individual users’ social influence on Twitter during the Egyptian Revolution of 2011. Following this lens, we suggest an extended model of sustained social influence (that considers retweets as the measure of user influence) as a function of the duality of individual Twitter users’ social actions and the underlying facilitating Twitter network structure. Based on an analysis of organic large-scale Twitter data on this social movement, we examine how characteristics of individuals’ social actions, namely activity and tenure on Twitter, and characteristics facilitated by the network (i.e., the number of followers as well as centrality in the community structure of Twitter), impact retweet influence in time windows spanning the movement. Utilizing a mixed methods approach consisting of machine learning and human coding we conceptualize social movement-related engagement activities of Twitter users, which map to generic frames of social movement mobilization. The analysis reveals interesting patterns across different contexts of the Egyptian Revolution. Regarding individual social action, social movement related to “who” and “where” activities, as well as tenure, were found to contribute to individual social influence. In terms of the facilitating structure, the follower network (an observed network structure) and centrality (an unobserved network structure) were both found to contribute significantly to sustained influence.

中文翻译:

社交媒体的影响:2011 年埃及革命期间推文的调查

通过社会运动理论的视角,本文研究了 2011 年埃及革命期间个人用户对 Twitter 的社会影响的驱动因素。根据这个视角,我们提出了一个持续社会影响的扩展模型(将转发视为用户的衡量标准)影响力)作为个人 Twitter 用户社交行为的二元性和潜在的促进 Twitter 网络结构的函数。基于对这一社会运动的有机大规模 Twitter 数据的分析,我们研究了个人社会行为的特征,即 Twitter 上的活动和任期,以及网络促进的特征(即追随者的数量和中心性)。在 Twitter 的社区结构中),在跨越运动的时间窗口中影响转发影响。利用由机器学习和人类编码组成的混合方法方法,我们将 Twitter 用户与社会运动相关的参与活动概念化,这些活动映射到社会运动动员的通用框架。分析揭示了埃及革命不同背景下的有趣模式。关于个人社会行动,与“谁”和“在哪里”活动以及任期相关的社会运动被发现有助于个人社会影响。在促进结构方面,追随者网络(观察到的网络结构)和中心性(未观察到的网络结构)都被发现对持续影响有显着贡献。映射到社会运动动员的一般框架。分析揭示了埃及革命不同背景下的有趣模式。关于个人社会行动,与“谁”和“在哪里”活动以及任期相关的社会运动被发现有助于个人社会影响。在促进结构方面,追随者网络(观察到的网络结构)和中心性(未观察到的网络结构)都被发现对持续影响有显着贡献。映射到社会运动动员的一般框架。分析揭示了埃及革命不同背景下的有趣模式。关于个人社会行动,与“谁”和“在哪里”活动以及任期相关的社会运动被发现有助于个人社会影响。在促进结构方面,追随者网络(观察到的网络结构)和中心性(未观察到的网络结构)都被发现对持续影响有显着贡献。
更新日期:2021-10-14
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