Abstract Misinformation online poses a range of threats, from subverting democratic processes to undermining public health measures. Proposed solutions encouraging more selective sharing by individuals removing false content and accounts that create or promote it. Here we provide framework evaluate interventions aimed at reducing viral misinformation both in isolation when used combination. We begin deriving generative model spread, inspired research on infectious disease. By applying this...

Understanding the spread of online rumors is a pressing societal challenge and an active area research across domains. In context 2022 U.S. midterm elections, one influential social media platform for sharing information — including that may be false, misleading, or unsubstantiated was Twitter (now renamed X). To increase understanding dynamics about we present analyze dataset 1.81 million posts corresponding to 135 distinct which during election season (September 5 December 1, 2022). We...

ABSTRACT Objective This study examines whether state‐linked sportswashing—through perceived associations between states and sports entities—can shield from public scrutiny over human rights abuses. We analyze changes in Chelsea F.C. supporters’ online behavior following Roman Abramovich's announcement to relinquish control of the club during Russia's invasion Ukraine. Method collected 700,000 tweets 7414 profiles London‐based English Premier League fans. Using a fine‐tuned BERT machine...

This study explores the dynamics of colorblind racism, intersectionality, and racially coded language in sports discourse on social media (Twitter/X), focusing contrasting public treatment African American athlete Angel Reese White Caitlin Clark before, during, after 2023 NCAA Women’s Basketball Championship. Analyzing 779,188 tweets using Large Language Model (LLM) RoBERTa, we identify distinct patterns fan interactions that reveal pervasive elements racism intersecting gender biases...

Abstract Can AI bolster state-backed propaganda campaigns, in practice? Growing use of and large language models has drawn attention to the potential for accompanying tools be used by malevolent actors. Though recent laboratory experimental evidence substantiated these concerns principle, usefulness production campaigns remained difficult ascertain. Drawing on adoption generative-AI techniques a state-affiliated site with ties Russia, we test whether enabled website amplify enhance its...

This paper introduces and presents a first analysis of uniquely curated dataset misinformation, disinformation, rumors spreading on Twitter about the 2020 U.S. election. Previous research misinformation—an umbrella term for false misleading content—has largely focused either broad categories, using finite set keywords to cover complex topic, or few, case studies, with increased precision but limited scope. Our approach, by comparison, leverages real-time reports collected from September...

Misinformation online poses a range of threats, from subverting democratic processes to undermining public health measures. Proposed solutions encouraging more selective sharing by individuals, platform removal false content and accounts that create or promote it. How, whether, which strategies implement depends on their relative combined ability reduce viral misinformation spread at practical levels enforcement. Here we provide framework evaluate interventions aimed reducing both in...

The 2020 United States (US) presidential election was — and has continued to be the focus of pervasive persistent mis- disinformation spreading through our media ecosystems, including social media. This event driven collection analysis large, directed network datasets, but such datasets can resist intuitive understanding. In large overwhelming number nodes edges present in typical representations create visual artifacts, as densely overlapping tightly-packed formations low-degree nodes,...

This paper introduces and presents a first analysis of uniquely curated dataset misinformation, disinformation, rumors spreading on Twitter about the 2020 U.S. Election. Previous research misinformation — an umbrella term for false misleading content has largely focused either broad categories, using finite set keywords to cover complex topic, or few, case studies, with increased precision but limited scope. Our approach, by comparison, leverages real-time reports collected from September...

The prevalence and spread of online misinformation during the 2020 US presidential election served to perpetuate a false belief in widespread fraud. Though much research has focused on how social media platforms connected people election-related rumors conspiracy theories, less is known about search engine pathways that linked users news content with potential undermine trust elections. In this paper, we present novel data related political headlines period. We scraped over 800,000 from...

Recent scholarship studying the impact of race-based prejudice has emphasized its rampant persistence throughout all aspects modern society, including world sports. Prior research from American leagues shown that even referees, trained officials intended to enact neutral judgements, are subject bias against Black and dark-skinned players. To extend these studies inform policies aimed at combating racial in public spaces more broadly, we report results a unique dataset over 6500 player-year...

The spread of false information on social media is a growing problem that has necessitated the development interventions to reduce its impact. We tested potential effectiveness “truth queries” — user replies draw attention truth as novel intervention for reducing impact shared media. Participants were shown Tweets containing appeared with queries (Experiments 1-3), no or unrelated 2-3) and asked judge either contained in Tweet their likelihood sharing it. consistently found belief reported...

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Fact-checking has been promoted as a key method for combating political misinformation. Comparing the spread of election-related misinformation narratives along with their relevant fact-checks, this study provides most comprehensive assessment to date real-world limitations faced by fact-checking efforts. To examine barriers impact, extends recent work from laboratory and experimental settings wider online information ecosystem present during 2022 U.S. midterm elections. From analyses...

The global reach of misinformation has exacerbated harms in low- and middle-income countries faced with deficiencies funding, platform engagement, media literacy. These challenges have reiterated the need for development strategies capable addressing that cannot be countered using popular fact-checking methods. Focusing on Kenya’s contentious 2022 election, we evaluate a novel method democratizing debunking efforts termed “social truth queries” (STQs), which use questions posed by everyday...

Wildlife conservancies across the globe are increasingly recognizing their need to support surrounding communities sustainably operate. Rapidly shifting environmental and sociopolitical climates stress existing resource service provisions, forcing wildlife co-manage with local shared resources like water, wildlife, soil, pollinators, security. This work presents a case study in Laikipia, Kenya on Ol Pejeta Conservancy's use of text-based technologies provide services build relationships many...

Recent scholarship studying the impact of racism and race-based prejudice has begun to elucidate its rampant persistence throughout all contexts modern society, including world sports. Prior research from American sports leagues shown that even referees, trained officials intended enact neutral judgements, are subject bias against Black dark-skinned players. To extend these studies inform policies aimed at combating racial in public spaces more broadly, we report results a unique dataset...

The 2020 United States presidential election was, and has continued to be, the focus of pervasive persistent mis- disinformation spreading through our media ecosystems, including social media. This event driven collection analysis large, directed network datasets, but such datasets can resist intuitive understanding. In large overwhelming number nodes edges present in typical representations create visual artifacts, as densely overlapping tightly-packed formations low-degree nodes, which...

Elections are assumed to provide legitimacy illiberal regimes. Yet why would obviously unfree elections increase citizens’ perceptions of regime strength or legitimacy? Synthesizing prior arguments, we conclude that many authors assume fraudulent can lead citizens upwardly adjust their assessment public support even when they suspect publicly documented election results be inflated. We note this hypothesis critically depends on ability independently evaluate sentiment. Given considerably...