{"title":"Generative AI Usage by Individuals During the 2024 U.S. Presidential Election: Symmetrical and Asymmetrical Analysis","authors":"Wanli Liu, Xuequn Wang, Yibai Li","doi":"10.1177/08944393251392913","DOIUrl":null,"url":null,"abstract":"With generative artificial intelligence’s (GenAI) growing popularity, individuals are increasingly using it when searching for election-related information. This scenario raises concerns that GenAI usage may result in widespread dissemination of misinformation, given its ability to generate seemingly authentic information. Nevertheless, despite the importance of Gen AI, few researchers have examined how individuals use this tool to search for election-related information. This study aims to assess how GenAI’s perceived system (i.e., accessibility and integration) and information quality (i.e., completeness, accuracy, and neutrality) impact its usage. Focusing on the 2024 U.S. presidential election, we conducted a two-wave survey and data was collected from 364 Americans. Participants were found to have a favorable attitude overall toward GenAI. Further, accuracy and neutrality were positively associated with GenAI usage. A fuzzy set qualitative comparative analysis was also conducted to identify different configurations of perceived system and information quality that led to high GenAI usage. Analyzing the qualitative responses further confirmed the results. This study contributes to the literature on the role of GenAI during elections, providing a nuanced understanding of how dimensions of GenAI’s perceived system and information quality impact individuals’ GenAI usage. The findings have significant practical implications for dealing with the (mis)information generated by GenAI.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"85 1","pages":""},"PeriodicalIF":4.3000,"publicationDate":"2025-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Social Science Computer Review","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1177/08944393251392913","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
With generative artificial intelligence’s (GenAI) growing popularity, individuals are increasingly using it when searching for election-related information. This scenario raises concerns that GenAI usage may result in widespread dissemination of misinformation, given its ability to generate seemingly authentic information. Nevertheless, despite the importance of Gen AI, few researchers have examined how individuals use this tool to search for election-related information. This study aims to assess how GenAI’s perceived system (i.e., accessibility and integration) and information quality (i.e., completeness, accuracy, and neutrality) impact its usage. Focusing on the 2024 U.S. presidential election, we conducted a two-wave survey and data was collected from 364 Americans. Participants were found to have a favorable attitude overall toward GenAI. Further, accuracy and neutrality were positively associated with GenAI usage. A fuzzy set qualitative comparative analysis was also conducted to identify different configurations of perceived system and information quality that led to high GenAI usage. Analyzing the qualitative responses further confirmed the results. This study contributes to the literature on the role of GenAI during elections, providing a nuanced understanding of how dimensions of GenAI’s perceived system and information quality impact individuals’ GenAI usage. The findings have significant practical implications for dealing with the (mis)information generated by GenAI.
期刊介绍:
Unique Scope Social Science Computer Review is an interdisciplinary journal covering social science instructional and research applications of computing, as well as societal impacts of informational technology. Topics included: artificial intelligence, business, computational social science theory, computer-assisted survey research, computer-based qualitative analysis, computer simulation, economic modeling, electronic modeling, electronic publishing, geographic information systems, instrumentation and research tools, public administration, social impacts of computing and telecommunications, software evaluation, world-wide web resources for social scientists. Interdisciplinary Nature Because the Uses and impacts of computing are interdisciplinary, so is Social Science Computer Review. The journal is of direct relevance to scholars and scientists in a wide variety of disciplines. In its pages you''ll find work in the following areas: sociology, anthropology, political science, economics, psychology, computer literacy, computer applications, and methodology.