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Community Topic Usage in Online Social Media

Published: 31 May 2020 Publication History

Abstract

Humans have a natural tendency to form social groups, and individual behaviours are thought to be strongly influenced by a salient sense of belonging to one or more such groups. It can be expected, therefore, that there will be behaviours that are specific to the group(s) to which a person currently feels they are interacting with and that some of these behaviours will manifest in topics and patterns of linguistic style associated with those groups. Here we explore this idea by attempting to identify group specific patterns of language usage in social media data from Twitter and Reddit. Topic models are used to infer patterns of language usage and group structures are either provided with the data (Reddit) inferred from the follower network (Twitter). We apply a Bayesian graphical model to infer community-topic associations, finding that substantially more coherent associations can often be identified than with a naive probability-based approach. Strong associations are found between groups and topics with both approaches, indicating that the methods used to (independently) identify groups and topics represent real underlying patterns of social communication and promising fruitful investigation of human social behaviour using these or similar techniques.

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Published In

cover image ACM Transactions on Social Computing
ACM Transactions on Social Computing  Volume 3, Issue 3
September 2020
94 pages
EISSN:2469-7826
DOI:10.1145/3403616
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

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Publication History

Published: 31 May 2020
Online AM: 07 May 2020
Accepted: 01 December 2019
Revised: 01 October 2019
Received: 01 November 2018
Published in TSC Volume 3, Issue 3

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Author Tags

  1. Social networks
  2. anorexia
  3. community detection
  4. eating disorders
  5. social representation theory
  6. topic models

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