Explaining Search Result Stances to Opinionated People
Zhangyi Wu,
Tim Draws,
Federico Cau
et al.
Abstract:published version features the final layout of the paper including the volume, issue and page numbers.
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“…Epstein and Robertson (2016) showed that the magnitude of SEME could be reduced to some extent by such alerts (cf. Tapinsky et al, 2018;Wu et al, 2023). Alerts of this sort could also be used to flag the rising tide of online "misinformation" -an imperfect but not entirely unreasonable method for appeasing free speech advocates without suppressing content (Nekmat, 2020;Shin et al, 2023;cf.…”
Recent studies have shown that biased search results can produce substantial shifts in the opinions and voting preferences of undecided voters – a phenomenon called the “search engine manipulation effect” (SEME), one of the most powerful list effects ever discovered. We believe this is so because, unlike other list effects, SEME is supported by a daily regimen of operant conditioning. When people conduct searches for simple facts (86% of searches), the correct answer invariably turns up in the top position, which teaches users to attend to and click on high-ranking search results. As a result, when people are undecided, they tend to formulate opinions based on web pages linked to top search results. We tested this hypothesis in a controlled experiment with 551 US voters. Participants in our High-Trust group conducted routine searches in which the correct answer always appeared in the first search result. In our Low-Trust group, the correct answer could appear in any search position other than the first two. In all, participants had to answer five questions during this pre-training, and we focused our analysis on people who answered all the questions correctly (n = 355) – in other words, on people who were maximally impacted by the pre-training contingencies. A difference consistent with our hypothesis emerged between the groups when they were subsequently asked to search for information on political candidates. Voting preferences in the High-Trust group shifted toward the favored candidate at a higher rate (34.6%) than voting preferences in the Low-Trust group (17.1%, p = 0.001).
“…Epstein and Robertson (2016) showed that the magnitude of SEME could be reduced to some extent by such alerts (cf. Tapinsky et al, 2018;Wu et al, 2023). Alerts of this sort could also be used to flag the rising tide of online "misinformation" -an imperfect but not entirely unreasonable method for appeasing free speech advocates without suppressing content (Nekmat, 2020;Shin et al, 2023;cf.…”
Recent studies have shown that biased search results can produce substantial shifts in the opinions and voting preferences of undecided voters – a phenomenon called the “search engine manipulation effect” (SEME), one of the most powerful list effects ever discovered. We believe this is so because, unlike other list effects, SEME is supported by a daily regimen of operant conditioning. When people conduct searches for simple facts (86% of searches), the correct answer invariably turns up in the top position, which teaches users to attend to and click on high-ranking search results. As a result, when people are undecided, they tend to formulate opinions based on web pages linked to top search results. We tested this hypothesis in a controlled experiment with 551 US voters. Participants in our High-Trust group conducted routine searches in which the correct answer always appeared in the first search result. In our Low-Trust group, the correct answer could appear in any search position other than the first two. In all, participants had to answer five questions during this pre-training, and we focused our analysis on people who answered all the questions correctly (n = 355) – in other words, on people who were maximally impacted by the pre-training contingencies. A difference consistent with our hypothesis emerged between the groups when they were subsequently asked to search for information on political candidates. Voting preferences in the High-Trust group shifted toward the favored candidate at a higher rate (34.6%) than voting preferences in the Low-Trust group (17.1%, p = 0.001).
Personalized news experiences powered by recommender systems permeate our lives and have the potential to influence not only our opinions, but also our decisions. At the same time, the content and viewpoints contained within news recommendations are driven by multiple factors, including both personalization and editorial selection. Explanations could help users gain a better understanding of the factors contributing to the news items selected for them to read. Indeed, recent works show that explanations are essential for users of news recommenders to understand their consumption preferences and set intentions in line with their goals, such as goals for knowledge development and increased diversity of content or viewpoints. We give examples of such works on explanation and interactive interface interventions which have been effective in influencing readers' consumption intentions and behaviors in news recommendations. However, the state‐of‐the‐art in news recommender systems currently fall short in terms of evaluating such interventions in live systems, limiting our ability to measure their true impact on user behavior and opinions. To help understand the true benefit of these interfaces, we therefore call for improving the realism of studies for news.
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