Tweeting in echo chambers? Analyzing Twitter discourse between American Jewish interest groups

Osterbur, Megan; Kiel, Christina

doi:10.1080/19331681.2020.1838396

Cited by 9 publications

(4 citation statements)

References 39 publications

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“…While most prior research has conceptualized echo chambers as clusters of individuals with congruent viewpoints, pinpointing the tendencies of individual users can prove challenging due to the privacy-sensitive nature of such information. In this study, we defined an echo chamber as a group of users who engaged in retweeting at least two related events ( Choi et al, 2020 ; Gao et al, 2023b ), with users who were @-mentioned by echo chamber members also considered part of the same echo chamber ( Osterbur and Kiel, 2021 ). The rationale for this definition stems from the varying impacts of distinct communication forms on social media.…”

Section: Methodsmentioning

confidence: 99%

Personality traits and their influence on Echo chamber formation in social media: a comparative study of Twitter and Weibo

Song,

Guo,

Gao

2024

Front. Psychol.

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The echo chamber effect on social media has attracted attention due to its potentially disruptive consequences on society. This study presents a framework to evaluate the impact of personality traits on the formation of echo chambers. Using Weibo and Twitter as platforms, we first define an echo chamber as a network where users interact solely with those sharing their opinions, and quantify echo chamber effects through selective exposure and homophily. We then employ an unsupervised personality recognition method to assign a personality model to each user, and compare the distribution differences of echo chambers and personality traits across platforms and topics. Our findings show that, although user personality trait models exhibit similar distributions between topics, differences exist between platforms. Among 243 personality model combinations, over 20% of Weibo echo chamber members are “ynynn” models, while over 15% of Twitter echo chamber members are “nnnny” models. This indicates significant differences in personality traits among echo chamber members between platforms. Specific personality traits attract like-minded individuals to engage in discussions on particular topics, ultimately forming homogeneous communities. These insights are valuable for developing targeted management strategies to prevent the spread of fake news or rumors.

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Section: Methodsmentioning

confidence: 99%

Personality traits and their influence on Echo chamber formation in social media: a comparative study of Twitter and Weibo

Song,

Guo,

Gao

2024

Front. Psychol.

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“…Since different forms of communication on social media tend to have different effects. The retweet function plays a crucial role in promoting polarization, and comments make an important contribution in building consensus 42 . However, the @ function is often used to initiate a conversation with a targeted user 43 .…”

Section: Methodsmentioning

confidence: 99%

Echo chamber effects on short video platforms

Gao

Liu

Gao

2023

Sci Rep

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In recent years, short videos have become an increasingly vital source of information. To compete for users’ attention, short video platforms have been overusing algorithmic technology, making the group polarization intensify, which is likely to push users into the homogeneous “echo chamber”. However, echo chambers can contribute to the spread of misleading information, false news, or rumors, which have negative social impacts. Therefore, it is necessary to explore echo chamber effects in short video platforms. Moreover, the communication paradigms between users and feed algorithms greatly vary across short video platforms. This paper investigated echo chamber effects of three popular short video platforms (Douyin, TikTok, and Bilibili) using social network analysis and explored how user features influenced the generation of echo chambers. We quantified echo chamber effects through two primary ingredients: selective exposure and homophily, in both platform and topic dimensions. Our analyses indicate that the gathering of users into homogeneous groups dominates online interactions on Douyin and Bilibili. We performed performance comparison of echo chamber effects and found that echo chamber members tend to display themselves to attract the attention of their peers and that cultural differences can prevent the development of echo chambers. Our findings are of great value in designing targeted management strategies to prevent the spread of misleading information, false news, or rumors.

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“…For the discovery of communities or groups of users with similar characteristics, the Clauset-Newman-Moore algorithm was used [50,51]. This algorithm uncovers communities within a network based on a topology that works by optimizing modularity.…”

Section: Gephimentioning

confidence: 99%

International Youth Movements for Climate Change: The #FridaysForFuture Case on Twitter

Castillo

Hernández

2022

Sustainability

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Agenda 2030 and Sustainable Development Goals (SDGs) are critical pieces of climate change communication. #FridaysForFuture (FFF) is one of the movements with the most coverage. This paper analyzes the network structure generated in Twitter by the interactions created by its users about the 23 September 2022 demonstrations, locates the most relevant users in the conversation based on multiple measures of intermediation and centrality of Social Network Analysis (SNA), identifies the most important topics of conversation regarding the #FridaysForFuture movement, and checks if the use of audio-visual content or links associated with the messages have a direct influence on the engagement. The NodeXL pro program was used for data collection and the different structures were represented using the Social Network Analysis method (SNA). Thanks to this methodology, the most relevant centrality measures were calculated: eigenvector centrality, betweenness centrality as relative measures, and the levels of indegree and outdegree as absolute measures. The network generated by the hashtag #FridaysforFuture consisted of a total of 12,136 users, who interacted on a total of 37,007 occasions. The type of action on the Twitter social network was distributed in five categories: 16,420 retweets, 14,866 mentions in retweets, 3151 mentions, 1584 tweets, and 986 replies. It is concluded that the number of communities is large and geographically distributed around the world, and the most successful accounts are so because of their relevance to those communities; the action of bots is tangible and is not demonized by the platform; some users can achieve virality without being influencers; the three languages that stood out are English, French, and German; and climate activism generates more engagement from users than the usual Twitter engagement average.

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Tweeting in echo chambers? Analyzing Twitter discourse between American Jewish interest groups

Cited by 9 publications

References 39 publications

Personality traits and their influence on Echo chamber formation in social media: a comparative study of Twitter and Weibo

Personality traits and their influence on Echo chamber formation in social media: a comparative study of Twitter and Weibo

Echo chamber effects on short video platforms

International Youth Movements for Climate Change: The #FridaysForFuture Case on Twitter

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