Confirmation Bias in Seeking Climate Information: Employing Relative Search Volume to Predict Partisan Climate Opinions

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

Social Science Computer Review Pub Date : 2023-03-03 DOI:10.1177/08944393231160963

Yifei Wang, Kokil Jaidka

{"title":"Confirmation Bias in Seeking Climate Information: Employing Relative Search Volume to Predict Partisan Climate Opinions","authors":"Yifei Wang, Kokil Jaidka","doi":"10.1177/08944393231160963","DOIUrl":null,"url":null,"abstract":"In an increasingly digitized world, online information-seeking (OIS) behaviors have reflected people’s intentions and constituted a critical component in synthesizing public opinion. Climate change is among the gravest threats facing the world today, and previous studies have adopted OIS data to gauge public interest in climate change. However, such studies have ignored the psychological attributes of search keywords and the role of social identities in influencing OIS. This study explores whether search strategies align with the expected confirmation biases of regions with different partisan beliefs. We use spatial web search trends to show the significant differences in the search keywords adopted by the Democrat-majority (“climate change”) versus the Republican-majority (“global warming”) regions of the United States. Furthermore, using the region-level search and survey data (2008–2018), we demonstrate that the preferential use of search keywords can predict climate opinions. This study concludes by discussing the significant findings and the open questions for future work.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":" ","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2023-03-03","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/10.1177/08944393231160963","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

In an increasingly digitized world, online information-seeking (OIS) behaviors have reflected people’s intentions and constituted a critical component in synthesizing public opinion. Climate change is among the gravest threats facing the world today, and previous studies have adopted OIS data to gauge public interest in climate change. However, such studies have ignored the psychological attributes of search keywords and the role of social identities in influencing OIS. This study explores whether search strategies align with the expected confirmation biases of regions with different partisan beliefs. We use spatial web search trends to show the significant differences in the search keywords adopted by the Democrat-majority (“climate change”) versus the Republican-majority (“global warming”) regions of the United States. Furthermore, using the region-level search and survey data (2008–2018), we demonstrate that the preferential use of search keywords can predict climate opinions. This study concludes by discussing the significant findings and the open questions for future work.

查看原文本刊更多论文

寻求气候信息的确认偏差:利用相对搜索量来预测党派气候意见

在日益数字化的世界中，在线信息寻求行为反映了人们的意图，并构成了综合民意的关键组成部分。气候变化是当今世界面临的最严重威胁之一，之前的研究采用了OIS数据来衡量公众对气候变化的兴趣。然而，这些研究忽视了搜索关键词的心理属性以及社会身份在影响OIS中的作用。这项研究探讨了搜索策略是否与不同党派信仰地区的预期确认偏差一致。我们使用空间网络搜索趋势来显示美国民主党占多数的地区（“气候变化”）与共和党占多数的区域（“全球变暖”）采用的搜索关键词的显著差异。此外，使用地区层面的搜索和调查数据（2008-2018），我们证明了优先使用搜索关键词可以预测气候意见。本研究最后讨论了重要的发现和未来工作中悬而未决的问题。

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.