ArticlePloS one2020
Using interpersonal communication strategies to encourage science conversations on social media.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Climate change perspectives in Lithuania: exploring science attitudes and personality correlations.Frontiers in psychology · 2026Article
- Using Social Media to Disseminate Behavior Change Interventions: Scoping Review of Systematic Reviews.Journal of medical Internet research · 2025Article
- Communicating biodiversity research on YouTube: An experimental comparison of scientists and third-party presenters.Public understanding of science (Bristol, England) · 2025Article
- Crowdsourcing conservation: unveiling Taiwan's sea turtle foraging grounds, emerging threats, and residency with broad societal engagement.BMC ecology and evolution · 2025Article
- Socioeconomic stratification in adolescent digital engagement: cultural capital, emotional mediation, and bilibili usage patterns in Chinese high schools.Frontiers in sociology · 2025Article
- Social media's impact on environmental awareness: a marginal treatment effect analysis of WeChat usage in China.BMC public health · 2024Article
- Engaging the public: English local government organisations' social media communications during the COVID-19 pandemic.Applied Corpus Linguistics · 2023Article
- How to improve public health literacy based on polycentric public goods theory: preferences of the Chinese general population.BMC public health · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Today, many science communicators are using social media to share scientific information with citizens, but, as research has shown, fostering conversational exchanges remains a challenge. This largely qualitative study investigated the communication strategies applied by individual scientists and environmental non-governmental organizations on Twitter and Instagram to determine whether particular social media practices encourage two-way conversations between science communicators and citizens. Data from Twitter and Instagram posts, interviews with the communicators, and a survey of audience members were triangulated to identify emergent communication strategies and the resulting engagement; provide insight into why particular practices are employed by communicators; and explain why audiences choose to participate in social media conversations with communicators. The results demonstrate that the application of interpersonal communication strategies encourage conversational engagement, in terms of the number of comments and unique individuals involved in conversations. In particular, using selfies (images and videos), non-scientific content, first person pronoun-rich captions, and responding to comments result in the formation of communicator-audience relationships, encouraging two-way conversations on social media. Furthermore, the results indicate that Instagram more readily supports the implementation of interpersonal communication strategies than Twitter, making Instagram the preferred platform for promoting conversational exchanges. These findings can be applicable to diverse communicators, subjects, audiences, and environments (online and offline) in initiatives to promote awareness and understanding of science.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.