The Influence of Political Fit, Issue Fit, and Targeted Political Advertising Disclosures on Persuasion Knowledge, Party Evaluation, and Chilling Effects

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

Social Science Computer Review Pub Date : 2023-09-12 DOI:10.1177/08944393231193731

Melanie Hirsch, Alice Binder, Jörg Matthes

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引用次数: 0

Abstract

The availability of online data has altered the role of social media. By offering targeted online advertising, that is, persuasive messages tailored to user groups, political parties profit from large data profiles to send fine-grained advertising appeals to susceptible voters. This between-subject experiment ( N = 421) investigates the influence of targeted political advertising disclosures (targeting vs. no-targeting disclosure), political fit (high vs. low), and issue fit (high vs. low) on recipients’ party evaluation and chilling effect intentions. The mediating role of targeting knowledge (TK) and perceived manipulative intent (PMI), two dimensions of persuasion knowledge, are investigated. The findings show that disclosing a targeting strategy and a high political fit activated individuals’ TK, that is, their recognition that their data had been used to show the ads, which then increased the evaluation of the political party and individuals’ intentions to engage in future chilling effect behaviors. High political fit decreased individuals’ reflections about the appropriateness of the targeted political ads (i.e., PMI), which then increased party evaluation. Issue fit did not affect individuals’ persuasion knowledge.

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政治契合度、议题契合度和针对性政治广告披露对说服知识、政党评价和寒蝉效应的影响

在线数据的可用性改变了社交媒体的角色。通过提供有针对性的在线广告，即针对用户群体量身定制的有说服力的信息，政党可以从大数据档案中获利，向易受影响的选民发送细粒度的广告吸引力。本被试间实验(N = 421)调查了有针对性的政治广告披露(有针对性与无针对性的披露)、政治契合度(高与低)和议题契合度(高与低)对接受者政党评价和寒战效应意图的影响。研究了说服知识的两个维度——目标知识(TK)和知觉操纵意图(PMI)的中介作用。研究结果表明，披露目标策略和高度的政治契合度激活了个人的TK，即他们对自己的数据被用于展示广告的认识，从而增加了对政党和个人参与未来寒蝉效应行为的意图的评估。高政治契合度降低了个人对目标政治广告恰当性的反思(即PMI)，进而提高了政党评价。议题契合度不影响个体的说服知识。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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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.