数据新闻与网络理论:通过 X(原 Twitter)互动研究政治传播

Alexandros Samalis, Alexandros Z. Spyropoulos, Georgios C. Makris, Charalambos Bratsas, A. Veglis, V. Tsiantos, Anthoula Baliou, Emmanouel Garoufallou, Anastasios Ventouris
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引用次数: 0

摘要

本研究探讨的研究问题是"希腊执政党内部的政治联系是如何发展的,通过对 X(原 Twitter)上的互动进行网络分析,可以发现哪些潜在的模式和动态?为了解决这些问题,我们从 X 上收集了数据,重点关注执政党内政治家的关注、转发和提及活动。我们使用源自数学中网络理论的工具对这些互动进行了细致的分析,这些工具包括中心度(in and out-strength centrality)、枢纽中心度(hubs and authorities centralities)、中心熵(in and out-vertex entropy)。与新兴的数据新闻领域相一致,这种方法提高了分析的严谨性和深度,有助于对复杂的政治格局有更细致入微的了解。研究结果揭示了复杂而动态的结构,这些结构可能反映了党内关系、传播策略以及反复发生的事件对这些联系的影响。因此,本研究为理解通过社交网络进行的政治传播提供了新的见解,并展示了网络理论和数据新闻技术在社会科学中的应用潜力。
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Data Journalism and Network Theory: A Study of Political Communication through X (Formerly Twitter) Interactions
This study investigates the research questions: “How do political connections within Greece’s governing party evolve, and what underlying patterns and dynamics are revealed through a network analysis of interactions on X (formerly Twitter)?” To address these questions, data were collected from X, focusing on following, retweeting, and mentioning activities among the politicians within the governing party. The interactions were meticulously analysed using tools derived from Network Theory in mathematics, including in and out-strength centrality, hubs and authorities centralities, and in and out-vertex entropy. In line with the emerging field of data journalism, this approach enhances the rigour and depth of analysis, facilitating a more nuanced understanding of complex political landscapes. The findings reveal complex and dynamic structures that may reflect internal relationships, communication strategies, and the influence of recurring events on these connections within the party. This study thus provides novel insights into understanding political communication via social networks and demonstrates the applicative potential of Network Theory and data journalism techniques in social sciences.
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