Using Twitter to Detect Polling Place Issue Reports on U.S. Election Days

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

Social Science Computer Review Pub Date : 2024-08-10 DOI:10.1177/08944393241269420

Prathm Juneja, Luciano Floridi

引用次数: 0

Abstract

In this article, we analyze whether Twitter can be used to detect relative reports of issues at polling places. We use 20,322 tweets geolocated to U.S. states that match a series of keywords on the 2010, 2012, 2014, 2016, and 2018 general election days. We fine-tune BERTweet, a pre-trained language model, using a training set of 6,365 tweets labeled as issues or non-issues. We develop a model with an accuracy of 96.9% and a recall of 72.2%, and another model with an accuracy of 90.5% and a recall of 93.5%, far exceeding the performance of baseline models. Based on these results, we argue that these BERTweet-based models are promising methods for detecting reports of polling place issues on U.S. election days. We suggest that outputs from these models can be used to supplement existing voter protection efforts and to research the impact of policies, demographics, and other variables on voting access.

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使用 Twitter 检测美国大选日投票站问题报告

在本文中，我们分析了 Twitter 是否可用于检测投票站问题的相关报告。我们使用了 2010、2012、2014、2016 和 2018 年大选日与一系列关键词相匹配的 20,322 条推文，这些推文的地理位置位于美国各州。我们使用标注为问题或非问题的 6365 条推文的训练集，对预先训练好的语言模型 BERTweet 进行了微调。我们开发的一个模型准确率为 96.9%，召回率为 72.2%，另一个模型准确率为 90.5%，召回率为 93.5%，远远超过基线模型的性能。基于这些结果，我们认为这些基于 BERTweet 的模型是检测美国大选日投票站问题报告的有效方法。我们建议，这些模型的输出结果可用于补充现有的选民保护工作，以及研究政策、人口统计和其他变量对投票机会的影响。

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.