Citizens’ Acceptance of Data-Driven Political Campaigning: A 25-Country Cross-National Vignette Study

IF 3 2区社会学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Social Science Computer Review Pub Date : 2024-05-01 DOI:10.1177/08944393241249708

Rens Vliegenthart, Jade Vrielink, Katharine Dommett, Rachel Gibson, Esmeralda Bon, Xiaotong Chu, Claes de Vreese, Sophie Lecheler, Jörg Matthes, Sophie Minihold, Lukas Otto, Marlis Stubenvoll, Sanne Kruikemeier

{"title":"Citizens’ Acceptance of Data-Driven Political Campaigning: A 25-Country Cross-National Vignette Study","authors":"Rens Vliegenthart, Jade Vrielink, Katharine Dommett, Rachel Gibson, Esmeralda Bon, Xiaotong Chu, Claes de Vreese, Sophie Lecheler, Jörg Matthes, Sophie Minihold, Lukas Otto, Marlis Stubenvoll, Sanne Kruikemeier","doi":"10.1177/08944393241249708","DOIUrl":null,"url":null,"abstract":"This paper investigates how the acceptance of data-driven political campaigning depends on four different message characteristics. A vignette study was conducted in 25 countries with a total of 14,390 respondents who all evaluated multiple descriptions of political advertisements. Relying on multi-level models, we find that in particular the source and the issue of the message matters. Messages that are sent by a party the respondent likes and deal with a political issue the respondent considers important are rated more acceptable. Furthermore, targeting based on general characteristics instead of individual ones is considered more acceptable, as is a general call to participate in the upcoming elections instead of a specific call to vote for a certain party. Effects differ across regulatory contexts, with the negative impact of both individual targeting and a specific call to vote for a certain party being in countries that have higher levels of legislative regulation.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"47 1","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2024-05-01","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/10.1177/08944393241249708","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

This paper investigates how the acceptance of data-driven political campaigning depends on four different message characteristics. A vignette study was conducted in 25 countries with a total of 14,390 respondents who all evaluated multiple descriptions of political advertisements. Relying on multi-level models, we find that in particular the source and the issue of the message matters. Messages that are sent by a party the respondent likes and deal with a political issue the respondent considers important are rated more acceptable. Furthermore, targeting based on general characteristics instead of individual ones is considered more acceptable, as is a general call to participate in the upcoming elections instead of a specific call to vote for a certain party. Effects differ across regulatory contexts, with the negative impact of both individual targeting and a specific call to vote for a certain party being in countries that have higher levels of legislative regulation.

查看原文本刊更多论文

公民对数据驱动的政治活动的接受程度：25 国跨国小故事研究

本文研究了数据驱动型政治竞选活动的接受程度如何取决于四种不同的信息特征。我们在 25 个国家开展了一项小故事研究，共有 14,390 名受访者对政治广告的多种描述进行了评估。通过多层次模型，我们发现信息的来源和问题尤为重要。由受访者喜欢的政党发出的、涉及受访者认为重要的政治问题的信息更容易被接受。此外，基于一般特征而非个别特征的定向信息被认为更容易被接受，正如一般呼吁参与即将到来的选举而非具体呼吁投票给某个政党一样。不同监管环境下的效果也不同，在立法监管水平较高的国家，针对个人和呼吁投票给某个政党的负面影响都较大。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Social Science Computer Review 社会科学-计算机：跨学科应用

CiteScore

9.00

自引率

4.90%

发文量

审稿时长

>12 weeks

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.