Do Voters Get the Information They Want? Understanding Authentic Voter FAQs in the US and How to Improve for Informed Electoral Participation

• URL: http://arxiv.org/abs/2412.15273v1
• Date: Tue, 17 Dec 2024 16:29:53 GMT
• Title: Do Voters Get the Information They Want? Understanding Authentic Voter FAQs in the US and How to Improve for Informed Electoral Participation
• Authors: Vipula Rawte, Deja N Scott, Gaurav Kumar, Aishneet Juneja, Bharat Sowrya Yaddanapalli, Biplav Srivastava,
• Abstract summary: In the US, state election commissions (SECs) are the primary providers of Frequently Asked Questions (FAQs) to voters. To the best of our knowledge, there is neither a single source with comprehensive FAQ nor a study analyzing the data at national level to identify current practices and ways to improve the status quo.
• Score: 4.9706015445291625
• License:
• Abstract: Accurate information is crucial for democracy as it empowers voters to make informed decisions about their representatives and keeping them accountable. In the US, state election commissions (SECs), often required by law, are the primary providers of Frequently Asked Questions (FAQs) to voters, and secondary sources like non-profits such as League of Women Voters (LWV) try to complement their information shortfall. However, surprisingly, to the best of our knowledge, there is neither a single source with comprehensive FAQs nor a study analyzing the data at national level to identify current practices and ways to improve the status quo. This paper addresses it by providing the {\bf first dataset on Voter FAQs covering all the US states}. Second, we introduce metrics for FAQ information quality (FIQ) with respect to questions, answers, and answers to corresponding questions. Third, we use FIQs to analyze US FAQs to identify leading, mainstream and lagging content practices and corresponding states. Finally, we identify what states across the spectrum can do to improve FAQ quality and thus, the overall information ecosystem. Across all 50 U.S. states, 12% were identified as leaders and 8% as laggards for FIQS\textsubscript{voter}, while 14% were leaders and 12% laggards for FIQS\textsubscript{developer}.

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