3/15/2023 0 Comments Secret animosity means![]() Placing citizens in the position of users narrows and isolates the perspective from the broader and more indirect political and environmental conditions and impacts of AI systems, such as the power structures of digital economies, the environmental impact of material production of digital technologies, and the impact on work-life (Crawford, 2021), or the significant risks of social media for mental health (Boer et al., 2020 Rathje et al., 2021) and democracy (Epstein and Robertson, 2015 Nemitz, 2018 Ledger of Harms, 2021). It truncates thinking and aligns it with the human-centered design standards, thus emphasizing the perspective of a human being as "a user", and people as "user groups". This project has important theoretical and democratic implications, and extends the use of trace data and computational methods in political behavior. Furthermore, examining how Twitter users react to these posts, we find that negative partisanship plays a greater role in online engagement: users are more likely to like and share politicians’ tweets negative toward the out-party than tweets positive toward the in-party. However, more ideologically extreme politicians and those in the opposition (i.e., the Democrats) are more negative toward the out-party than those ideologically moderate and whose party is in power. Although politicians post many tweets negative toward the out-party, they post more tweets positive toward their in-party. Relying on 1,195,844 tweets sent by 564 political elites (i.e., members of US House and Senate, Presidential and Vice-Presidential nominees from 2000 to 2020, and members of the Trump Cabinet) and machine learning to reliably classify the tone of the tweets, we show that elite expressions online are driven by positive partisanship more than negative partisanship. Unlike past work, which relies on survey self-reports or experimental designs among ordinary citizens, this pre-registered project examines actual social media expressions of an exhaustive list of American politicians as well as citizens’ engagement with these posts. It remains unclear, however, whether in-party affinity (i.e., positive partisanship) or out-party animosity (i.e., negative partisanship) more strongly influences political attitudes and behaviors. The report includes a model of the impacts of COVID‑19 misinformation on vaccination rates in Canada, producing quantitative estimates of its impacts on our health and the economy, and situating these within a broader context of societal and economic harms.Īmericans view their in-party members positively and out-party members negatively. ![]() It explores what makes us susceptible to misinformation and how we might use these insights to improve societal resilience to it. Strategies and tools exist to help combat these harms, strengthen, and build trust in our institutions, and boost our ability to recognize and reject the misinformation we encounter.įault Lines details how science and health misinformation can proliferate and its impacts on individuals, communities, and society. The pervasive spread of misinformation and the damage it can cause underscore the need for reasoned, evidence-informed decision-making at both the personal and public level. These harms often fall most heavily on the most vulnerable. Science and health misinformation damages our community well-being through otherwise preventable illnesses, deaths, and economic losses, and our social well-being through polarization and the erosion of public trust. We are particularly vulnerable to misinformation in times of crisis when the consequences are most acute. Because it’s designed to appeal to our emotions and exploit our cognitive shortcuts, everyone is susceptible to it. Misinformation can cause significant harm to individuals, communities, and societies.
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