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As artificial intelligence (AI)-powered technology enables the efficient processing of large volumes of comments, more companies, including news publications, are experimenting with and adopting AI moderation to manage their commenting platforms. However, the resulting user experiences have been largely underexplored in relation to these technical advances in comments section management. This study used an experiment to examine the impact of AI filters on individuals' perceptions about comments sections (i.e., bias, credibility, positive and negative affect, and use intention). The findings indicate that AI moderation had statistically significant impacts on perceived credibility and use intention. Beyond the main effects, priming with a deceptive comment issue moderated the impacts of comment filtering on user perceptions as well. [ABSTRACT FROM AUTHOR]

This study aims to evaluate how individuals are prepared to cope with or plan for their afterlife digital footprints, by examining how (1) access, (2) literacy, and (3) preparedness for digital afterlife work in concert to influence one's wellbeing. We found the indirect relationship between access and wellbeing and the influence of digital literacy on wellbeing was indirect, illustrating that the key to the puzzle is in the sequential step in which digital literacy incubates the readiness to cope with digital remains, which influences one's subjective wellbeing. One of the most unrecognized challenges facing digital traces is the exploitation of post-life remain of data, as the question of who accesses, owns, or controls personal data after death remains largely unanswered. We argue that the preparedness for digital afterlife represents a new form of social concern with real-life consequences, or even a newer space for inequality debates. [ABSTRACT FROM AUTHOR]

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Asynchronous, anonymous online debaters might be less likely than face-to-face debaters to value their public self-image (face), and thus disagree more freely. In this study, we examined whether polite disagreements (as opposed to rude ones) help online debaters win over audience members. An analysis of the most voted-on 100 political debates on Debate.org (200 debaters; 1,750 voters; 472,652 words) showed that debate initiators who used politer face-saving strategies to disagree (i.e., using expressions such as negatives with agree words rather than disagree or harsh rejection words) were more likely to receive more audience votes and win their debates. These results suggest that politeness tactics during online debates increase effectiveness, align with normative ideals, and yield pragmatic gain. [ABSTRACT FROM AUTHOR]

Humans are not very good at detecting deception. The problem is that there is currently no other particular way to distinguish fake opinions in a comments section than by resorting to poor human judgments. For years, most scholarly and industrial efforts have been directed at detecting fake consumer reviews of products or services. A technique for identifying deceptive opinions on social issues is largely underexplored and undeveloped. Inspired by the need for a reliable deceptive comment detection method, this study aims to develop an automated machine-learning technique capable of determining opinion trustworthiness in a comment section. In the process, we have created the first large-scale ground truth dataset consisting of 866 truthful and 869 deceptive comments on social issues. This is also one of the first attempts to detect comment deception in Asian languages (in Korean, specifically). The proposed machine-learning technique achieves nearly 81% accuracy in detecting untruthful opinions about social issues. This performance is quite consistent across issues and well beyond that of human judges. [ABSTRACT FROM AUTHOR]

Personal lies (girl on date lying to dad) and fake news (Obama Bans Pledge of Allegiance) both deceive but in different ways, so they require different detection methods. People in long-term relationships try to tell undetectable lies to encourage, often, audience inaction. In contrast, unattached fake news welcome attention and try to ignite audience action. Thus, they differ in six ways: (a) speaker–audience relationship, (b) goal, (c) emotion, (d) information, (e) number of participants, and (f) citation of sources. To detect personal lies, a person can use their intimate relationship to heighten emotions, raise the stakes, and ask for more information, participants, or sources. In contrast, a person evaluates the legitimacy of potential fake news by examining the websites of its author, the people in the news article, and/or reputable media sources. Large social media companies have suitable expertise, data, and resources to reduce fake news. Search tools, rival news media links to one another's articles, encrypted signature links, and improved school curricula might also help users detect fake news. [ABSTRACT FROM AUTHOR]

This study proposes the idea of justificatory information forefending, a cognitive process by which individuals accept information that confirms their preexisting health beliefs, and reject information that is dissonant with their attitudes. In light of the sheer volume of often contradictory information related to health that is frequently highlighted by the traditional media, this study sought to identify antecedents and outcomes of this justificatory information forefending. Results indicate that individuals who are exposed to contradictory health information, currently engage in risky health behavior, are comfortable using the Internet to search for information, and are currently taking steps to maintain their health are likely to actively select health information that confirms their preexisting notions about their health, and to reject information that is contradictory to their beliefs. Additionally, individuals who engage in justificatory information forefending were also found to continue to engage in risky health behavior. Implications for theory and practice are discussed. [ABSTRACT FROM AUTHOR]