Meaningful Context, a Red Flag, or Both? Preferences for Enhanced Misinformation Warnings Among US Twitter Users

Sharevski, Filipo; Devine, Amy; Jachim, Peter; Pieroni, Emma

doi:10.1145/3549015.3555671

Cited by 15 publications

(11 citation statements)

References 46 publications

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“…Among the reported geographical regions USA is the highest reported region in ( N = 19 ~ 68%) studies. 19 , 30 , 32 , 33 , 35 , 37 , 38 , 40 , 42 The second highest reported region for longitudinal analysis is the UK and reported in ( N = 8 ~ 29%) research studies. 22 , 23 , 33 , 34 , 38 , 41 , 44 , 46 India and Pakistan reported in retrospective studies 22 , 34 , 38 for users’ behavior analysis toward vaccination.…”

Section: Resultsmentioning

confidence: 99%

Longitudinal analysis of behavioral factors and techniques used to identify vaccine hesitancy among Twitter users: Scoping review

Khan,

Biswas,

Shah

2023

Human Vaccines & Immunotherapeutics

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While vaccines have played a pivotal role in the fight against infectious diseases, individuals engage in online resources to find vaccine-related support and information. The benefits and consequences of these online peers are unclear and mainly cause a behavioral shift in user sentiment toward vaccination. This scoping review aims to identify the community and individual factors that longitudinally influence public behavior toward vaccination. The secondary aim is to gain insight into techniques and methodologies used to extract these factors from Twitter data. We followed PRISMA-ScR guidelines to search various online repositories. From this search process, a total of 28 most relevant articles out of 705 relevant studies. Three main themes emerged including individual and community factors influencing public attitude toward vaccination, and techniques employed to identify these factors. Anti-vax, Pro-vax, and neutral are the major communities, while misinformation, vaccine campaign, and user demographics are the common individual factors assessed during this reviewing process. Twitter user sentiment (positive, negative, and neutral) and emotions (fear, trust, sadness) were also discussed to identify the intentions to accept or refuse vaccines. SVM, LDA, BERT are the techniques used for topic modeling, while Louvain, NodeXL, and Infomap algorithms are used for community detection. This research is notable for being the first systematic review that emphasizes the dearth of longitudinal studies and the methodological and underlying practical constraints underpinning the lucrative implementation of an explainable and longitudinal behavior analysis system. Moreover, new possible research directions are suggested for the researchers to perform accurate human behavior analysis.

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Section: Resultsmentioning

confidence: 99%

Longitudinal analysis of behavioral factors and techniques used to identify vaccine hesitancy among Twitter users: Scoping review

Khan,

Biswas,

Shah

2023

Human Vaccines & Immunotherapeutics

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“…The hacktivists' resoluteness to go after the misinformers would certainly have implications for the content/user moderation on social media, user participation, and future of Internet activism overall. Moderating users and content on social media was, and still is, the response by the mainstream platforms to the political and public health misinformation [108]. Alternative platforms like Gab, Gettr, and Parler, seen as the seeding grounds for this misinformation [133], on the other hand, never did, nor currently do, employ any content/user moderation [107].…”

Section: Discussionmentioning

confidence: 99%

“…In the original version of trolling and meme sharing the misinformation was seen as an alternative expression of disagreement, revolt, or ridicule without any context, but the contemporary trolling and memes is brought in the political context as a ready-made content for expression of political attitudes [90]. Despite that fact checking is widely available (and even suggested to users when content is moderated on social media [108]), the political appropriation of misinformation thrives because "people won't fact check things and perpetuate them as long as these things align with their political ideology" [P2]. The reason why most social media users "fall for misinformation" is plain ignorance and stubbornness to hear anything contrary to their own political opinions" [P3] which results from "a serious lack of, at least in the U.S, critical thinking education in schools [P2].…”

Section: Mental Models Of Misinformationmentioning

confidence: 99%

“…An algorithmic is also available for the mainstream social media platforms (the alternative ones do not deem misinformation as a problem [107]) that leverages natural language processing, image analysis, or metadata to detect trolling and memes [50,51,122]. Platforms also have the option for algorithmic "soft" moderation by either obscuring trolling and memes with warnings covers or attaching warning labels [108,125] and "hard" moderation for removing or suspending misinformer accounts [63]. None of these solutions, however fends of troll farms and meme disseminators effectively, so we wanted to know what hacktivists have to propose instead in the second research question.…”

Section: Active Countering Of Misinformationmentioning

confidence: 99%

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Folk Models of Misinformation on Social Media

Sharevski¹,

Devine²,

Pieroni³

et al. 2023

Proceedings 2023 Network and Distributed System Security Symposium

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In this study, we interviewed 22 prominent hacktivists to learn their take on the increased proliferation of misinformation on social media. We found that none of them welcomes the nefarious appropriation of trolling and memes for the purpose of political (counter)argumentation and dissemination of propaganda. True to the original hacker ethos, misinformation is seen as a threat to the democratic vision of the Internet, and as such, it must be confronted on the face with tried hacktivists' methods like deplatforming the "misinformers" and doxing or leaking data about their funding and recruitment. The majority of the hacktivists also recommended interventions for raising misinformation literacy in addition to targeted hacking campaigns. We discuss the implications of these findings relative to the emergent recasting of hacktivism in defense of a constructive and factual social media discourse.

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“…Using in-context warnings to improve users' safety awareness and encourage users to take protection measures can be considered a form of "digital nudging" [26,160]. More recently, researchers have also adapted in-context security warnings to nudge social media users to recognize and avoid online disinformation [85,163] and reflect before posting potentially harmful content [88,169,200]. Beyond platform-initiated integration of warnings, end-users also voluntarily seek in-context alert interfaces for productivity improvement.…”

Section: In Situ Alerting Toolsmentioning

confidence: 99%

Farsight: Fostering Responsible AI Awareness During AI Application Prototyping

Wang,

Kulkarni,

Wilcox

et al. 2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

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Fig. 1: With in situ interfaces and novel techniques, Farsight empowers AI prototypers to envision potential harms that may arise from their large language models (LLMs)-powered AI applications during early prototyping. (A) In this example, an AI prototyper is creating a prompt for an English-to-French translator in a web-based AI prototyping tool. (B) The Alert Symbol from Farsight warns the user of potential risks associated with their AI application. (C) Clicking the symbol expands the Awareness Sidebar, highlighting news articles relevant to the user's prompt (top), and LLM-generated potential use cases and harms (bottom). (D) Clicking the blue button opens the Harm Envisioner that allows the user to interactively envision, assess, and reflect on the potential use cases, stakeholders, and harms of their AI application with the assistance of an LLM.

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Meaningful Context, a Red Flag, or Both? Preferences for Enhanced Misinformation Warnings Among US Twitter Users

Cited by 15 publications

References 46 publications

Longitudinal analysis of behavioral factors and techniques used to identify vaccine hesitancy among Twitter users: Scoping review

Longitudinal analysis of behavioral factors and techniques used to identify vaccine hesitancy among Twitter users: Scoping review

Folk Models of Misinformation on Social Media

Farsight: Fostering Responsible AI Awareness During AI Application Prototyping

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