research-article

What makes you tick? The psychology of social media engagement in space science communication

Authors:

Martin Van Kranendonk,

Yanir SeroussiAuthors Info & Claims

Computers in Human Behavior, Volume 68, Issue C

Pages 480 - 492

https://doi.org/10.1016/j.chb.2016.11.068

Published: 01 March 2017 Publication History

Abstract

The rise of social media has transformed the way the public engages with science organisations and scientists. Retweet, Like, Share and Comment are a few ways users engage with messages on Twitter and Facebook, two of the most popular social media platforms. Despite the availability of big data from these digital footprints, research into social media science communication is scant. This paper presents a novel empirical study into the features of engaging science-related social media messages, focusing on space science communications. It is hypothesised that these messages contain certain psycholinguistic features that are unique to the field of space science. We built a predictive model to forecast the engagement levels of social media posts. By using four feature sets (n-grams, psycholinguistics, grammar and social media), we were able to achieve prediction accuracies in the vicinity of 90% using three supervised learning algorithms (Naive Bayes, linear classifier and decision tree). We conducted the same experiments on social media messages from three other fields (politics, business and non-profit) and discovered several features that are exclusive to space science communications: anger, authenticity, hashtags, visual descriptionsbe it visual perception-related words, or media elementsand a tentative tone. Big data analysis to study social media engagement in space science communication.Machine learning predicted social media message engagement level with 90% accuracy.Engaging social media space science posts contain features unique to space science.These features are anger, authenticity, visual description and a tentative tone.

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Cited By

Nasr ARashidirad MYoganathan VSadaghiani A(2024)CSR marketing through social media and contextual effects on stakeholder engagement: a multinational cross-industry analysisInformation Systems Frontiers10.1007/s10796-022-10273-626:3(987-1004)Online publication date: 1-Jun-2024
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Published In

cover image Computers in Human Behavior

Computers in Human Behavior Volume 68, Issue C

March 2017

564 pages

ISSN:0747-5632

Issue’s Table of Contents

Copyright © Elsevier Ltd.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 March 2017

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Cited By

Nasr ARashidirad MYoganathan VSadaghiani A(2024)CSR marketing through social media and contextual effects on stakeholder engagement: a multinational cross-industry analysisInformation Systems Frontiers10.1007/s10796-022-10273-626:3(987-1004)Online publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1007/s10796-022-10273-6
Bär DCalderon FLawlor MLicklederer STotzauer MFeuerriegel SHorvát ÁHall WContractor NFröhling LOgnayova KTaneja HWeber IGligori? KMejova Y(2023)Analyzing Social Media Activities at BellingcatProceedings of the 15th ACM Web Science Conference 202310.1145/3578503.3583604(163-173)Online publication date: 30-Apr-2023
https://dl.acm.org/doi/10.1145/3578503.3583604
Fang BZhang FHou LHu EZhang JShen JChen Y(2022)A Proposed Method for Predicting User Disinformation Forwarding BehaviorScientific Programming10.1155/2022/92160632022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/9216063
Schreiner MFischer TRiedl R(2021)Impact of content characteristics and emotion on behavioral engagement in social media: literature review and research agendaElectronic Commerce Research10.1007/s10660-019-09353-821:2(329-345)Online publication date: 1-Jun-2021
https://dl.acm.org/doi/10.1007/s10660-019-09353-8
Lai ILiu Y(2020)The effects of content likeability, content credibility, and social media engagement on users' acceptance of product placement in mobile social networksJournal of Theoretical and Applied Electronic Commerce Research10.4067/S0718-1876202000030010215:3(1-17)Online publication date: 14-Feb-2020
https://dl.acm.org/doi/10.4067/S0718-18762020000300102

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