Chuanhui Wu , Yifan Wang , Yuchen Zhang , Houcai Wang , Yufei Pang
{"title":"用人工智能对抗仇恨:人工智能生成的反言论如何帮助对抗社交媒体上的仇恨言论?","authors":"Chuanhui Wu , Yifan Wang , Yuchen Zhang , Houcai Wang , Yufei Pang","doi":"10.1016/j.tele.2025.102304","DOIUrl":null,"url":null,"abstract":"<div><div>In the digital age, the interconnected nature of social media has accelerated the exchange of information, knowledge, and ideas. However, it has also amplified the spread of hate speech. Although user-generated content is considered a potential solution to online hate speech, it also presents challenges such as inefficiency, error rates, and ethical risks to users. Therefore, this study focuses on the impact of AI-generated counterspeech on user engagement intention to confront hate speech on social media. Through a pilot study and three experiments (<em>N</em> = 809), we empirically demonstrate the effectiveness of AI-generated counterspeech. Study 1 shows that participants are more willing to engage in counterspeech when it is present than in hate speech with no counterspeech. Study 2 reveals that empathy-based counterspeech elicits greater engagement than fact-based counterspeech and that AI-generated counterspeech has a stronger impact on user engagement intention. Study 3 indicates that participants are more willing to engage with AI-generated counterspeech when the AI identity is not disclosed. Perceived trust mediates the effects of generator types and identity disclosure on user engagement. Our findings provide empirical evidence of the application of AI in online hate speech governance and offer practical insights for social media platforms.</div></div>","PeriodicalId":48257,"journal":{"name":"Telematics and Informatics","volume":"101 ","pages":"Article 102304"},"PeriodicalIF":8.3000,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Confront hate with AI: how AI-generated counter speech helps against hate speech on social Media?\",\"authors\":\"Chuanhui Wu , Yifan Wang , Yuchen Zhang , Houcai Wang , Yufei Pang\",\"doi\":\"10.1016/j.tele.2025.102304\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In the digital age, the interconnected nature of social media has accelerated the exchange of information, knowledge, and ideas. However, it has also amplified the spread of hate speech. Although user-generated content is considered a potential solution to online hate speech, it also presents challenges such as inefficiency, error rates, and ethical risks to users. Therefore, this study focuses on the impact of AI-generated counterspeech on user engagement intention to confront hate speech on social media. Through a pilot study and three experiments (<em>N</em> = 809), we empirically demonstrate the effectiveness of AI-generated counterspeech. Study 1 shows that participants are more willing to engage in counterspeech when it is present than in hate speech with no counterspeech. Study 2 reveals that empathy-based counterspeech elicits greater engagement than fact-based counterspeech and that AI-generated counterspeech has a stronger impact on user engagement intention. Study 3 indicates that participants are more willing to engage with AI-generated counterspeech when the AI identity is not disclosed. Perceived trust mediates the effects of generator types and identity disclosure on user engagement. Our findings provide empirical evidence of the application of AI in online hate speech governance and offer practical insights for social media platforms.</div></div>\",\"PeriodicalId\":48257,\"journal\":{\"name\":\"Telematics and Informatics\",\"volume\":\"101 \",\"pages\":\"Article 102304\"},\"PeriodicalIF\":8.3000,\"publicationDate\":\"2025-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Telematics and Informatics\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0736585325000668\",\"RegionNum\":2,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Telematics and Informatics","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0736585325000668","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
Confront hate with AI: how AI-generated counter speech helps against hate speech on social Media?
In the digital age, the interconnected nature of social media has accelerated the exchange of information, knowledge, and ideas. However, it has also amplified the spread of hate speech. Although user-generated content is considered a potential solution to online hate speech, it also presents challenges such as inefficiency, error rates, and ethical risks to users. Therefore, this study focuses on the impact of AI-generated counterspeech on user engagement intention to confront hate speech on social media. Through a pilot study and three experiments (N = 809), we empirically demonstrate the effectiveness of AI-generated counterspeech. Study 1 shows that participants are more willing to engage in counterspeech when it is present than in hate speech with no counterspeech. Study 2 reveals that empathy-based counterspeech elicits greater engagement than fact-based counterspeech and that AI-generated counterspeech has a stronger impact on user engagement intention. Study 3 indicates that participants are more willing to engage with AI-generated counterspeech when the AI identity is not disclosed. Perceived trust mediates the effects of generator types and identity disclosure on user engagement. Our findings provide empirical evidence of the application of AI in online hate speech governance and offer practical insights for social media platforms.
期刊介绍:
Telematics and Informatics is an interdisciplinary journal that publishes cutting-edge theoretical and methodological research exploring the social, economic, geographic, political, and cultural impacts of digital technologies. It covers various application areas, such as smart cities, sensors, information fusion, digital society, IoT, cyber-physical technologies, privacy, knowledge management, distributed work, emergency response, mobile communications, health informatics, social media's psychosocial effects, ICT for sustainable development, blockchain, e-commerce, and e-government.