从边缘网络社区看模因的起源

Savvas Zannettou, T. Caulfield, Jeremy Blackburn, Emiliano De Cristofaro, Michael Sirivianos, G. Stringhini, Guillermo Suarez-Tangil
{"title":"从边缘网络社区看模因的起源","authors":"Savvas Zannettou, T. Caulfield, Jeremy Blackburn, Emiliano De Cristofaro, Michael Sirivianos, G. Stringhini, Guillermo Suarez-Tangil","doi":"10.1145/3278532.3278550","DOIUrl":null,"url":null,"abstract":"Internet memes are increasingly used to sway and manipulate public opinion. This prompts the need to study their propagation, evolution, and influence across the Web. In this paper, we detect and measure the propagation of memes across multiple Web communities, using a processing pipeline based on perceptual hashing and clustering techniques, and a dataset of 160M images from 2.6B posts gathered from Twitter, Reddit, 4chan's Politically Incorrect board (/pol/), and Gab, over the course of 13 months. We group the images posted on fringe Web communities (/pol/, Gab, and The_Donald subreddit) into clusters, annotate them using meme metadata obtained from Know Your Meme, and also map images from mainstream communities (Twitter and Reddit) to the clusters. Our analysis provides an assessment of the popularity and diversity of memes in the context of each community, showing, e.g., that racist memes are extremely common in fringe Web communities. We also find a substantial number of politics-related memes on both mainstream and fringe Web communities, supporting media reports that memes might be used to enhance or harm politicians. Finally, we use Hawkes processes to model the interplay between Web communities and quantify their reciprocal influence, finding that /pol/ substantially influences the meme ecosystem with the number of memes it produces, while The_Donald has a higher success rate in pushing them to other communities.","PeriodicalId":20640,"journal":{"name":"Proceedings of the Internet Measurement Conference 2018","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"215","resultStr":"{\"title\":\"On the Origins of Memes by Means of Fringe Web Communities\",\"authors\":\"Savvas Zannettou, T. Caulfield, Jeremy Blackburn, Emiliano De Cristofaro, Michael Sirivianos, G. Stringhini, Guillermo Suarez-Tangil\",\"doi\":\"10.1145/3278532.3278550\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Internet memes are increasingly used to sway and manipulate public opinion. This prompts the need to study their propagation, evolution, and influence across the Web. In this paper, we detect and measure the propagation of memes across multiple Web communities, using a processing pipeline based on perceptual hashing and clustering techniques, and a dataset of 160M images from 2.6B posts gathered from Twitter, Reddit, 4chan's Politically Incorrect board (/pol/), and Gab, over the course of 13 months. We group the images posted on fringe Web communities (/pol/, Gab, and The_Donald subreddit) into clusters, annotate them using meme metadata obtained from Know Your Meme, and also map images from mainstream communities (Twitter and Reddit) to the clusters. Our analysis provides an assessment of the popularity and diversity of memes in the context of each community, showing, e.g., that racist memes are extremely common in fringe Web communities. We also find a substantial number of politics-related memes on both mainstream and fringe Web communities, supporting media reports that memes might be used to enhance or harm politicians. Finally, we use Hawkes processes to model the interplay between Web communities and quantify their reciprocal influence, finding that /pol/ substantially influences the meme ecosystem with the number of memes it produces, while The_Donald has a higher success rate in pushing them to other communities.\",\"PeriodicalId\":20640,\"journal\":{\"name\":\"Proceedings of the Internet Measurement Conference 2018\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"215\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Internet Measurement Conference 2018\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3278532.3278550\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Internet Measurement Conference 2018","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3278532.3278550","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 215

摘要

网络表情包越来越多地被用来左右和操纵公众舆论。这促使我们有必要研究它们在整个网络中的传播、演变和影响。在本文中,我们使用基于感知哈希和聚类技术的处理管道,以及从Twitter, Reddit, 4chan's political Incorrect board (/pol/)和Gab收集的26条帖子中收集的1.6亿张图片的数据集,在13个月的时间里,检测和测量了模因在多个Web社区中的传播。我们将边缘网络社区(/pol/, Gab和The_Donald subreddit)上发布的图片分组,使用Know Your meme获得的meme元数据对其进行注释,并将主流社区(Twitter和Reddit)的图片映射到集群中。我们的分析对每个社区背景下模因的受欢迎程度和多样性进行了评估,结果显示,例如,种族主义模因在边缘网络社区中极为普遍。我们还在主流和边缘网络社区中发现了大量与政治相关的模因,这支持了媒体关于模因可能被用来提升或伤害政治家的报道。最后,我们使用Hawkes过程来模拟网络社区之间的相互作用,并量化它们的相互影响,发现/pol/通过其产生的模因数量实质性地影响了模因生态系统,而The_Donald在将它们推送到其他社区方面具有更高的成功率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
On the Origins of Memes by Means of Fringe Web Communities
Internet memes are increasingly used to sway and manipulate public opinion. This prompts the need to study their propagation, evolution, and influence across the Web. In this paper, we detect and measure the propagation of memes across multiple Web communities, using a processing pipeline based on perceptual hashing and clustering techniques, and a dataset of 160M images from 2.6B posts gathered from Twitter, Reddit, 4chan's Politically Incorrect board (/pol/), and Gab, over the course of 13 months. We group the images posted on fringe Web communities (/pol/, Gab, and The_Donald subreddit) into clusters, annotate them using meme metadata obtained from Know Your Meme, and also map images from mainstream communities (Twitter and Reddit) to the clusters. Our analysis provides an assessment of the popularity and diversity of memes in the context of each community, showing, e.g., that racist memes are extremely common in fringe Web communities. We also find a substantial number of politics-related memes on both mainstream and fringe Web communities, supporting media reports that memes might be used to enhance or harm politicians. Finally, we use Hawkes processes to model the interplay between Web communities and quantify their reciprocal influence, finding that /pol/ substantially influences the meme ecosystem with the number of memes it produces, while The_Donald has a higher success rate in pushing them to other communities.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Reducing Permission Requests in Mobile Apps A Look at the ECS Behavior of DNS Resolvers RPKI is Coming of Age: A Longitudinal Study of RPKI Deployment and Invalid Route Origins Scanning the Scanners: Sensing the Internet from a Massively Distributed Network Telescope Learning Regexes to Extract Router Names from Hostnames
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1