Scientists as Influencers: The Role of Source Identity, Self-Disclosure, and Anti-Intellectualism in Science Communication on Social Media

Zhang, Annie L.; Lu, Hang

doi:10.1177/20563051231180623

Cited by 5 publications

(2 citation statements)

References 65 publications

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“…In an endeavor to understand how to divulge innovation, previous studies have proposed several factors that contribute to enhance engagement. These factors include the use of charismatic language (Tur et al ., 2022), the establishment of a clear and recognizable source identity, the perception of authenticity in communication, and the fostering of para-social interactions (Zhang and Lu, 2023).…”

Section: Conceptual Analysismentioning

confidence: 99%

Better abstract or concrete, narrating or not: optimal strategies for the communication of innovation

Cardamone,

Miceli,

Raimondo

2024

EJIM

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PurposeThis paper investigates how two characteristics of language, abstractness vs concreteness and narrativity, influence user engagement in communication exercises on innovation targeted to the general audience. The proposed conceptual model suggests that innovation fits well with more abstract language because of the association of innovation with imagination and distal construal. Moreover, communication of innovation may benefit from greater adherence to the narrativity arc, that is, early staging, increasing plot progression and climax optimal point. These effects are moderated by content variety and emotional tone, respectively.Design/methodology/approachBased on a Latent Dirichlet allocation (LDA) application on a sample of 3225 TED Talks transcripts, the authors identify 287 TED Talks on innovation, and then applied econometric analyses to test the hypotheses on the effects of abstractness vs concreteness and narrativity on engagement, and on the moderation effects of content variety and emotional tone.FindingsThe authors found that abstractness (vs concreteness) and narrativity have positive effects on engagement. These two effects are stronger with higher content variety and more positive emotional tone, respectively.Research limitations/implicationsThis paper extends the literature on communication of innovation, linguistics and text analysis by evaluating the roles of abstractness vs concreteness and narrativity in shaping appreciation of innovation.Originality/valueThis paper reports conceptual and empirical analyses on innovation dissemination through a popular medium – TED Talks – and applies modern text analysis algorithms to test hypotheses on the effects of two pivotal dimensions of language on user engagement.

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Section: Conceptual Analysismentioning

confidence: 99%

Better abstract or concrete, narrating or not: optimal strategies for the communication of innovation

Cardamone,

Miceli,

Raimondo

2024

EJIM

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“…In this meaning, regulatory capture has a cultural or value-driven dimension that encompasses 'intellectual, ideological, or political forms of dominance' (Saltelli et al, 2022). In a landscape where special interest groups are increasingly represented by popular science communicators, a lot of questions arise in relation to the power exercised by the rising impact of science influencers, whether from academic, journalism and industry environments (Zhang and Lu, 2023).…”

Section: Scientific Expertise Social Media and Regulatory Capturementioning

confidence: 99%

Regulation and NLP (RegNLP): Taming Large Language Models

Goanta,

Aletras,

Chalkidis

et al. 2023

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

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The scientific innovation in Natural Language Processing (NLP) and more broadly in artificial intelligence (AI) is at its fastest pace to date. As large language models (LLMs) unleash a new era of automation, important debates emerge regarding the benefits and risks of their development, deployment and use. Currently, these debates have been dominated by often polarized narratives mainly led by the AI Safety and AI Ethics movements. This polarization, often amplified by social media, is swaying political agendas on AI regulation and governance and posing issues of regulatory capture. Capture occurs when the regulator advances the interests of the industry it is supposed to regulate, or of special interest groups rather than pursuing the general public interest. Meanwhile in NLP research, attention has been increasingly paid to the discussion of regulating risks and harms. This often happens without systematic methodologies or sufficient rooting in the disciplines that inspire an extended scope of NLP research, jeopardizing the scientific integrity of these endeavors. Regulation studies are a rich source of knowledge on how to systematically deal with risk and uncertainty, as well as with scientific evidence, to evaluate and compare regulatory options. This resource has largely remained untapped so far. In this paper, we argue how NLP research on these topics can benefit from proximity to regulatory studies and adjacent fields. We do so by discussing basic tenets of regulation, and risk and uncertainty, and by highlighting the shortcomings of current NLP discussions dealing with risk assessment. Finally, we advocate for the development of a new multidisciplinary research space on regulation and NLP (RegNLP), focused on connecting scientific knowledge to regulatory processes based on systematic methodologies. 5476, Online. Association for Computational Linguistics.

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Navigating dual stigmas on social media: How self-disclosure strategies influence public attitudes toward sexual minorities with mental disorders

Lu,

2024

New Media & Society

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In light of the rising trend of self-disclosing stigmatized identities on social media and the insufficient understanding of its repercussions on societal attitudes, this study employs an intersectional framework to examine the impact of revealing dual stigmas related to sexual identities and health conditions on destigmatization. Drawing upon the intergroup contact hypothesis and social penetration theory, a national sample of U.S. adults ( N = 1,596) participated in a 3 (sexual identity cue: explicit-cue vs implicit-cue vs no-cue) × 5 (coping with mental disorders: good-coping vs balanced-coping vs poor-coping vs no-coping vs control) between-subjects experiment. Results revealed that while dual stigma disclosure occasionally showed enhanced positive impacts, it never exacerbated stigmatized attitudes compared to single stigma disclosure. In addition, the two self-disclosure strategies interacted to influence destigmatization, mediated by perceived competence rather than perceived authenticity. Implications from the findings are provided.

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Scientists as Influencers: The Role of Source Identity, Self-Disclosure, and Anti-Intellectualism in Science Communication on Social Media

Cited by 5 publications

References 65 publications

Better abstract or concrete, narrating or not: optimal strategies for the communication of innovation

Better abstract or concrete, narrating or not: optimal strategies for the communication of innovation

Regulation and NLP (RegNLP): Taming Large Language Models

Navigating dual stigmas on social media: How self-disclosure strategies influence public attitudes toward sexual minorities with mental disorders

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