SICLApr 24, 2024

Inside the echo chamber: Linguistic underpinnings of misinformation on Twitter

arXiv:2404.15925v14 citationsh-index: 7WebSci
Originality Synthesis-oriented
AI Analysis

This research addresses the problem of misinformation spread on social media for users and platforms, but it is incremental as it builds on existing work on echo chambers and linguistic analysis.

The study investigated how language use mediates conversations around misinformation on Twitter, finding increased group identity signals and processing fluency within echo chambers during such discussions.

Social media users drive the spread of misinformation online by sharing posts that include erroneous information or commenting on controversial topics with unsubstantiated arguments often in earnest. Work on echo chambers has suggested that users' perspectives are reinforced through repeated interactions with like-minded peers, promoted by homophily and bias in information diffusion. Building on long-standing interest in the social bases of language and linguistic underpinnings of social behavior, this work explores how conversations around misinformation are mediated through language use. We compare a number of linguistic measures, e.g., in-/out-group cues, readability, and discourse connectives, within and across topics of conversation and user communities. Our findings reveal increased presence of group identity signals and processing fluency within echo chambers during discussions of misinformation. We discuss the specific character of these broader trends across topics and examine contextual influences.

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