CLJul 6, 2023

Exploring Linguistic Style Matching in Online Communities: The Role of Social Context and Conversation Dynamics

Stanford
arXiv:2307.02758v2223 citationsh-index: 42
Originality Synthesis-oriented
AI Analysis

This research addresses the problem of understanding social influence and community dynamics in online platforms like Reddit for researchers and platform designers, but it is incremental as it builds on existing LSM concepts in a new context.

The study tackled the relationship between linguistic style matching (LSM) and online communication outcomes on Reddit by analyzing a large corpus of two-party conversation threads, examining how LSM varies with social factors like post features, conversation depth, user tenure, and controversiality, and measuring changes after community banning, revealing interplay with community metrics.

Linguistic style matching (LSM) in conversations can be reflective of several aspects of social influence such as power or persuasion. However, how LSM relates to the outcomes of online communication on platforms such as Reddit is an unknown question. In this study, we analyze a large corpus of two-party conversation threads in Reddit where we identify all occurrences of LSM using two types of style: the use of function words and formality. Using this framework, we examine how levels of LSM differ in conversations depending on several social factors within Reddit: post and subreddit features, conversation depth, user tenure, and the controversiality of a comment. Finally, we measure the change of LSM following loss of status after community banning. Our findings reveal the interplay of LSM in Reddit conversations with several community metrics, suggesting the importance of understanding conversation engagement when understanding community dynamics.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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