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Bibliographic Details
Main Author: Yang, Wen
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2404.15631
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author Yang, Wen
author_facet Yang, Wen
contents This study investigates echo chambers in social networks through an analysis of Twitter news accounts. Utilizing bias labels from the AllSides website, we construct a dataset representing six dimensions of news bias. Through manual extraction of follower/following relationships, we analyze interactions among 65 active Twitter news accounts. Despite the relatively small size of the network node data utilized, results reveal distinct clustering patterns indicative of echo chambers, with limited interaction between conflicting ideologies. This study underscores the potential impact of bias on information dissemination and democratic expression. These findings offer valuable insights into the dynamics of echo chambers in contemporary social media environments.
format Preprint
id arxiv_https___arxiv_org_abs_2404_15631
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Are There Echo Chambers in the US News Ecosystem? Evidence From Twitter/X
Yang, Wen
Social and Information Networks
This study investigates echo chambers in social networks through an analysis of Twitter news accounts. Utilizing bias labels from the AllSides website, we construct a dataset representing six dimensions of news bias. Through manual extraction of follower/following relationships, we analyze interactions among 65 active Twitter news accounts. Despite the relatively small size of the network node data utilized, results reveal distinct clustering patterns indicative of echo chambers, with limited interaction between conflicting ideologies. This study underscores the potential impact of bias on information dissemination and democratic expression. These findings offer valuable insights into the dynamics of echo chambers in contemporary social media environments.
title Are There Echo Chambers in the US News Ecosystem? Evidence From Twitter/X
topic Social and Information Networks
url https://arxiv.org/abs/2404.15631