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一个关于社交媒体用户对宗教错误信息参与度的数据集。

A dataset on social media users' engagement with religious misinformation.

作者信息

Al-Zaman Md Sayeed, Noman Mridha Md Shiblee

机构信息

Department of Journalism and Media Studies, Jahangirnagar University, Savar, Dhaka 1342, Bangladesh.

出版信息

Data Brief. 2023 Jul 22;49:109439. doi: 10.1016/j.dib.2023.109439. eCollection 2023 Aug.

DOI:10.1016/j.dib.2023.109439
PMID:37554994
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10405184/
Abstract

This dataset comprises Facebook data on five cases of religious misinformation in Bangladesh. To the best of our knowledge, it is the first publicly accessible dataset on Facebook-based religious misinformation in the country, featuring 7350 comments contributed by unique users. As online religious misinformation has been implicated in causing interreligious violence and tension in Bangladesh, this dataset can offer crucial insights into how social media is being exploited to foment such events. It may also help advance policy reform and activism to protect human rights and prevent the spread of religious misinformation.

摘要

该数据集包含了关于孟加拉国五起宗教错误信息的脸书数据。据我们所知,这是该国首个可公开获取的基于脸书的宗教错误信息数据集,有7350条由不同用户贡献的评论。由于在线宗教错误信息在孟加拉国被认为是引发宗教间暴力和紧张局势的原因之一,该数据集可以为社交媒体如何被用于煽动此类事件提供关键见解。它还可能有助于推动政策改革和维权行动,以保护人权并防止宗教错误信息的传播。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f730/10405184/c9be3484b90c/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f730/10405184/c9be3484b90c/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f730/10405184/c9be3484b90c/gr1.jpg

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本文引用的文献

1
ToxLex_bn: A curated dataset of bangla toxic language derived from Facebook comment.ToxLex_bn:一个从脸书评论中提取的孟加拉语有毒语言的精选数据集。
Data Brief. 2022 Jun 24;43:108416. doi: 10.1016/j.dib.2022.108416. eCollection 2022 Aug.
2
Interrater reliability: the kappa statistic.组内一致性:kappa 统计量。
Biochem Med (Zagreb). 2012;22(3):276-82.