Do you hear the people sing? Comparison of synchronized URL and narrative themes in 2020 and 2023 French protests.

IF 2.4 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

Frontiers in Big Data Pub Date : 2023-08-24 eCollection Date: 2023-01-01 DOI:10.3389/fdata.2023.1221744

Lynnette Hui Xian Ng, Kathleen M Carley

{"title":"Do you hear the people sing? Comparison of synchronized URL and narrative themes in 2020 and 2023 French protests.","authors":"Lynnette Hui Xian Ng, Kathleen M Carley","doi":"10.3389/fdata.2023.1221744","DOIUrl":null,"url":null,"abstract":"Introduction: France has seen two key protests within the term of President Emmanuel Macron: one in 2020 against Islamophobia, and another in 2023 against the pension reform. During these protests, there is much chatter on online social media platforms like Twitter.Methods: In this study, we aim to analyze the differences between the online chatter of the 2 years through a network-centric view, and in particular the synchrony of users. This study begins by identifying groups of accounts that work together through two methods: temporal synchronicity and narrative similarity. We also apply a bot detection algorithm to identify bots within these networks and analyze the extent of inorganic synchronization within the discourse of these events.Results: Overall, our findings suggest that the synchrony of users in 2020 on Twitter is much higher than that of 2023, and there are more bot activity in 2020 compared to 2023.","PeriodicalId":52859,"journal":{"name":"Frontiers in Big Data","volume":"6 ","pages":"1221744"},"PeriodicalIF":2.4000,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10483998/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Big Data","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fdata.2023.1221744","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}

引用次数: 0

Abstract

Introduction: France has seen two key protests within the term of President Emmanuel Macron: one in 2020 against Islamophobia, and another in 2023 against the pension reform. During these protests, there is much chatter on online social media platforms like Twitter.

Methods: In this study, we aim to analyze the differences between the online chatter of the 2 years through a network-centric view, and in particular the synchrony of users. This study begins by identifying groups of accounts that work together through two methods: temporal synchronicity and narrative similarity. We also apply a bot detection algorithm to identify bots within these networks and analyze the extent of inorganic synchronization within the discourse of these events.

Results: Overall, our findings suggest that the synchrony of users in 2020 on Twitter is much higher than that of 2023, and there are more bot activity in 2020 compared to 2023.

Abstract Image

查看原文本刊更多论文

你听到人民在歌唱吗？2020 年和 2023 年法国抗议活动中同步 URL 和叙事主题的比较。

导言：在埃马纽埃尔-马克龙总统的任期内，法国发生了两次重要的抗议活动：一次是 2020 年的反对伊斯兰恐惧症活动，另一次是 2023 年的反对养老金改革活动。在这些抗议活动期间，推特等网络社交媒体平台上出现了大量的讨论：在本研究中，我们旨在通过以网络为中心的视角，特别是用户的同步性，分析这两年网络讨论的差异。本研究首先通过时间同步性和叙事相似性这两种方法来识别共同工作的账户群。我们还应用了一种机器人检测算法来识别这些网络中的机器人，并分析了这些事件话语中的无机同步程度：总体而言，我们的研究结果表明，推特上 2020 年用户的同步性远高于 2023 年，而且 2020 年的机器人活动多于 2023 年。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Frontiers in Big Data Multiple-

CiteScore

5.20

自引率

3.20%

发文量

122

审稿时长

13 weeks