量化网络政治言论中的两极分化

IF 3 2区 计算机科学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Pau Muñoz, Alejandro Bellogín, Raúl Barba-Rojas, Fernando Díez
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引用次数: 0

摘要

在政治两极分化日益加剧的时代,分析政治两极分化对了解民主动态至关重要。本文介绍了对 2011 年至 2019 年西班牙选举周期内 X(推特)上的政治极化进行测量的综合研究。本文对用于识别和衡量微博平台上两极分化或争议的算法进行了广泛的比较分析。该分析专门针对政党官方账户在竞选前、竞选期间、选举日和选举后一周发布的信息。在比较评估结果的指导下,我们提出了一种更适合捕捉政治事件中极化现象的新算法,并通过真实数据进行了验证。因此,我们的研究为政治科学、社会网络分析和整个计算社会科学领域提供了一种捕捉网络政治言论中极化现象的现实方法,从而为这一领域做出了重大贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Quantifying polarization in online political discourse

Quantifying polarization in online political discourse

In an era of increasing political polarization, its analysis becomes crucial for the understanding of democratic dynamics. This paper presents a comprehensive research on measuring political polarization on X (Twitter) during election cycles in Spain, from 2011 to 2019. A wide comparative analysis is performed on algorithms used to identify and measure polarization or controversy on microblogging platforms. This analysis is specifically tailored towards publications made by official political party accounts during pre-campaign, campaign, election day, and the week post-election. Guided by the findings of this comparative evaluation, we propose a novel algorithm better suited to capture polarization in the context of political events, which is validated with real data. As a consequence, our research contributes a significant advancement in the field of political science, social network analysis, and overall computational social science, by providing a realistic method to capture polarization from online political discourse.

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来源期刊
EPJ Data Science
EPJ Data Science MATHEMATICS, INTERDISCIPLINARY APPLICATIONS -
CiteScore
6.10
自引率
5.60%
发文量
53
审稿时长
13 weeks
期刊介绍: EPJ Data Science covers a broad range of research areas and applications and particularly encourages contributions from techno-socio-economic systems, where it comprises those research lines that now regard the digital “tracks” of human beings as first-order objects for scientific investigation. Topics include, but are not limited to, human behavior, social interaction (including animal societies), economic and financial systems, management and business networks, socio-technical infrastructure, health and environmental systems, the science of science, as well as general risk and crisis scenario forecasting up to and including policy advice.
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