{"title":"基于和困惑:在网络上追踪一个模因短语的政治含义","authors":"S. Hagen, D. de Zeeuw","doi":"10.1177/20539517231163175","DOIUrl":null,"url":null,"abstract":"Current research on the weaponisation of far-right discourse online has mostly focused on the dangers of normalising hate speech. However, this often operates on questionable assumptions about how far-right terms retain problematic meanings over time and across different platforms. Yet contextual meaning-change, we argue, is key to assessing the normalisation of problematic but fuzzy terms as they spread across the Web. To redress this, our article traces the changing meaning of the term based, a word that was appropriated from Black Twitter to become a staple of online far-right slang in the mid-2010s. Through a quali-quantitative cross-platform approach, we analyse the evolution of the term between 2010 and 2021 on Twitter, Reddit and 4chan. We find that while the far right meaning of based partially survived, its meaning changed and was rendered diffuse as it was adopted by other communities, afforded by a repurposable kernel of meaning to based as ‘not caring about what other people think’ and ‘being true to yourself’ to which different (political) connotations were attached. This challenges the understanding of far-right memes and hate speech as carrying a single and persistent problematic message, and instead emphasises their varied meanings and subcultural functions within specific online communities.","PeriodicalId":47834,"journal":{"name":"Big Data & Society","volume":" ","pages":""},"PeriodicalIF":6.5000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Based and confused: Tracing the political connotations of a memetic phrase across the web\",\"authors\":\"S. Hagen, D. de Zeeuw\",\"doi\":\"10.1177/20539517231163175\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Current research on the weaponisation of far-right discourse online has mostly focused on the dangers of normalising hate speech. However, this often operates on questionable assumptions about how far-right terms retain problematic meanings over time and across different platforms. Yet contextual meaning-change, we argue, is key to assessing the normalisation of problematic but fuzzy terms as they spread across the Web. To redress this, our article traces the changing meaning of the term based, a word that was appropriated from Black Twitter to become a staple of online far-right slang in the mid-2010s. Through a quali-quantitative cross-platform approach, we analyse the evolution of the term between 2010 and 2021 on Twitter, Reddit and 4chan. We find that while the far right meaning of based partially survived, its meaning changed and was rendered diffuse as it was adopted by other communities, afforded by a repurposable kernel of meaning to based as ‘not caring about what other people think’ and ‘being true to yourself’ to which different (political) connotations were attached. This challenges the understanding of far-right memes and hate speech as carrying a single and persistent problematic message, and instead emphasises their varied meanings and subcultural functions within specific online communities.\",\"PeriodicalId\":47834,\"journal\":{\"name\":\"Big Data & Society\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":6.5000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Big Data & Society\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://doi.org/10.1177/20539517231163175\",\"RegionNum\":1,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"SOCIAL SCIENCES, INTERDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Big Data & Society","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1177/20539517231163175","RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL SCIENCES, INTERDISCIPLINARY","Score":null,"Total":0}
Based and confused: Tracing the political connotations of a memetic phrase across the web
Current research on the weaponisation of far-right discourse online has mostly focused on the dangers of normalising hate speech. However, this often operates on questionable assumptions about how far-right terms retain problematic meanings over time and across different platforms. Yet contextual meaning-change, we argue, is key to assessing the normalisation of problematic but fuzzy terms as they spread across the Web. To redress this, our article traces the changing meaning of the term based, a word that was appropriated from Black Twitter to become a staple of online far-right slang in the mid-2010s. Through a quali-quantitative cross-platform approach, we analyse the evolution of the term between 2010 and 2021 on Twitter, Reddit and 4chan. We find that while the far right meaning of based partially survived, its meaning changed and was rendered diffuse as it was adopted by other communities, afforded by a repurposable kernel of meaning to based as ‘not caring about what other people think’ and ‘being true to yourself’ to which different (political) connotations were attached. This challenges the understanding of far-right memes and hate speech as carrying a single and persistent problematic message, and instead emphasises their varied meanings and subcultural functions within specific online communities.
期刊介绍:
Big Data & Society (BD&S) is an open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities, and computing and their intersections with the arts and natural sciences. The journal focuses on the implications of Big Data for societies and aims to connect debates about Big Data practices and their effects on various sectors such as academia, social life, industry, business, and government.
BD&S considers Big Data as an emerging field of practices, not solely defined by but generative of unique data qualities such as high volume, granularity, data linking, and mining. The journal pays attention to digital content generated both online and offline, encompassing social media, search engines, closed networks (e.g., commercial or government transactions), and open networks like digital archives, open government, and crowdsourced data. Rather than providing a fixed definition of Big Data, BD&S encourages interdisciplinary inquiries, debates, and studies on various topics and themes related to Big Data practices.
BD&S seeks contributions that analyze Big Data practices, involve empirical engagements and experiments with innovative methods, and reflect on the consequences of these practices for the representation, realization, and governance of societies. As a digital-only journal, BD&S's platform can accommodate multimedia formats such as complex images, dynamic visualizations, videos, and audio content. The contents of the journal encompass peer-reviewed research articles, colloquia, bookcasts, think pieces, state-of-the-art methods, and work by early career researchers.