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Tomás Cicchini

Publications and source records attributed to Tomás Cicchini.

2 recordsLinked to original sources

Evaluating the Relationship Between News Source Sharing and Political Beliefs

In an era marked by an abundance of news sources, access to information significantly influences public opinion. Notably, the bias of news sources often serves as an indicator of individuals' political leanings. This study explores this hypothesis by examining the news sharing behavior of politically active social media users, whose political ideologies were identified in a previous study. Using correspondence analysis, we estimate the Media Sharing Index (MSI), a measure that captures bias in media outlets and user preferences within a hidden space. During Argentina's 2019 election on Twitter, we observed a predictable pattern: center-right individuals predominantly shared media from center-right biased outlets. However, it is noteworthy that those with center-left inclinations displayed a more diverse media consumption, which is a significant finding. Despite a noticeable polarization based on political affiliation observed in a retweet network analysis, center-left users showed more diverse media sharing preferences, particularly concerning the MSI. Although these findings are specific to Argentina, the developed methodology can be applied in other countries to assess the correlation between users' political leanings and the media they share.

cs.SI

Robustness of the public transport network against attacks on its routes

We investigate the robustness of Public Transport Networks (PTNs) when subjected to route attacks, focusing specifically on public bus lines. Such attacks, mirroring real-world scenarios, offer insight into the multifaceted dynamics of cities. Our study delves into the consequences of systematically removing entire routes based on strategies that use centrality measures. We evaluate the network's robustness by analyzing the sizes of fragmented networks, focusing on the largest components and derived metrics. To assess the efficacy of various attack strategies, we employ them on both a synthetic PTN model and a real-world example, specifically the Buenos Aires Metropolitan Area in Argentina. We examine these strategies and contrast them with random, and one-step most and least harmful procedures. Our findings indicate that \textit{betweenness}-based attacks and the one-step most (\textit{maximal}) harmful procedure emerge as the most effective attack strategies. Remarkably, the \textit{betweenness} strategy partitions the network into components of similar sizes, whereas alternative approaches yield one dominant and several minor components.

physics.soc-ph