Online network organization of Barcelona en Comú, an emergent movement-party.

Q1 Mathematics
Computational Social Networks Pub Date : 2017-01-01 Epub Date: 2017-09-18 DOI:10.1186/s40649-017-0044-4
Pablo Aragón, Helena Gallego, David Laniado, Yana Volkovich, Andreas Kaltenbrunner
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引用次数: 5

Abstract

The emerging grassroots party Barcelona en Comú won the 2015 Barcelona City Council election. This candidacy was devised by activists involved in the Spanish 15M movement to transform citizen outrage into political change. On the one hand, the 15M movement was based on a decentralized structure. On the other hand, political science literature postulates that parties develop oligarchical leadership structures. This tension motivates to examine whether Barcelona en Comú preserved a decentralized structure or adopted a conventional centralized organization. In this study we develop a computational methodology to characterize the online network organization of every party in the election campaign on Twitter. Results on the network of retweets reveal that, while traditional parties are organized in a single cluster, for Barcelona en Comú two well-defined groups co-exist: a centralized cluster led by the candidate and party accounts, and a decentralized cluster with the movement activists. Furthermore, results on the network of replies also shows a dual structure: a cluster around the candidate receiving the largest attention from other parties, and another with the movement activists exhibiting a higher predisposition to dialogue with other parties.

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在线网络组织巴塞罗那en Comú,一个新兴的运动党。
新兴的草根政党Barcelona en Comú赢得了2015年巴塞罗那市议会选举。这一候选资格是由参与西班牙15M运动的活动人士设计的,目的是将公民的愤怒转化为政治变革。一方面,15M运动是建立在分权结构的基础上的。另一方面,政治科学文献假设政党发展寡头领导结构。这种紧张关系促使人们审视巴塞罗那(Comú)是否保留了分散的结构,还是采用了传统的集中组织。在这项研究中,我们开发了一种计算方法来描述Twitter上竞选活动中每个政党的在线网络组织。转发网络的结果显示,虽然传统政党是在一个集群中组织的,但对于Barcelona en Comú来说,两个定义明确的群体并存:由候选人和政党账户领导的集中式集群,以及由运动活动家领导的分散集群。此外,在回复网络上的结果也显示出双重结构:一组围绕着获得其他政党最大关注的候选人,另一组围绕着运动积极分子表现出与其他政党对话的更高倾向。
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来源期刊
Computational Social Networks
Computational Social Networks Mathematics-Modeling and Simulation
自引率
0.00%
发文量
0
审稿时长
13 weeks
期刊介绍: Computational Social Networks showcases refereed papers dealing with all mathematical, computational and applied aspects of social computing. The objective of this journal is to advance and promote the theoretical foundation, mathematical aspects, and applications of social computing. Submissions are welcome which focus on common principles, algorithms and tools that govern network structures/topologies, network functionalities, security and privacy, network behaviors, information diffusions and influence, social recommendation systems which are applicable to all types of social networks and social media. Topics include (but are not limited to) the following: -Social network design and architecture -Mathematical modeling and analysis -Real-world complex networks -Information retrieval in social contexts, political analysts -Network structure analysis -Network dynamics optimization -Complex network robustness and vulnerability -Information diffusion models and analysis -Security and privacy -Searching in complex networks -Efficient algorithms -Network behaviors -Trust and reputation -Social Influence -Social Recommendation -Social media analysis -Big data analysis on online social networks This journal publishes rigorously refereed papers dealing with all mathematical, computational and applied aspects of social computing. The journal also includes reviews of appropriate books as special issues on hot topics.
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