Analyzing X's Web of Influence: Dissecting News Sharing Dynamics through Credibility and Popularity with Transfer Entropy and Multiplex Network Measures

TL;DR

This paper introduces a non-parametric Transfer Entropy framework combined with multiplex network measures to analyze influence dynamics among social media users, revealing patterns in news credibility and influence during major events.

Contribution

It advances influence analysis by integrating Transfer Entropy with multiplex network measures to identify key influencers and their news credibility strategies in large-scale social media networks.

Findings

Actors using trustworthy news sometimes rely on untrustworthy sources.

Influence patterns vary across different events and news categories.

Asymmetry exists in the use of trustworthy versus untrustworthy news for influence.

Abstract

The dissemination of news articles on social media platforms significantly impacts the public's perception of global issues, with the nature of these articles varying in credibility and popularity. The challenge of measuring this influence and identifying key propagators is formidable. Traditional graph-based metrics such as different centrality measures and node degree methods offer some insights into information flow but prove insufficient for identifying hidden influencers in large-scale social media networks such as X (previously known as Twitter). This study adopts and enhances a non-parametric framework based on Transfer Entropy to elucidate the influence relationships among X users. It further categorizes the distribution of influence exerted by these actors through the innovative use of multiplex network measures within a social media context, aiming to pinpoint influential actors during significant world events. The methodology was applied to three distinct events, and the findings revealed that actors in different events leveraged different types of news articles and influenced distinct sets of actors based on the news category. Notably, we found that actors disseminating trustworthy news articles to influence others occasionally resort to untrustworthy sources. However, the converse scenario, wherein actors predominantly using untrustworthy news types switch to trustworthy sources for influence, is less prevalent. This asymmetry suggests a discernible pattern in the strategic use of news articles for influence across social media networks, highlighting the nuanced roles of trustworthiness and popularity in the spread of information and influence.