Abstract
In this paper we investigate how users can be perceived on Twitter by looking at a selection of tweets, and how the type of personality traits and language can effect trust. We present participants with a selection of tweets and gather their initial opinions of the Twitter users presented by using a Likert scale (https://www.simplypsychology.org/likert-scale.html) and free text box for participants to share their opinions, hosted on Microsoft forms. This paper presents preliminary results based on the data gathered from a questionnaire created by the researcher, highlighting factors that impact how participants perceived the Twitter users. It was found that participants valued content, profile pictures and the display name more than likes and retweets. They did not like the more aggressive or opinionated users and had more of a neutral or positive reaction to the more light-hearted users.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Wang, P., Angarita, R., Renna, I.: Is this the era of misinformation yet: combining social bots and fake news to deceive the masses. In: Companion Proceedings of the The Web Conference 2018. International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, CHE, pp. 1557–1561 (2018)
Rosenberg, H., Syed, S., Rezaie, S.: The Twitter pandemic: the critical role of Twitter in the dissemination of medical information and misinformation during the COVID-19 pandemic. CJEM 22(4), 418–421 (2020). https://doi.org/10.1017/cem.2020.361
Qiu, L., Lin, Q., Ramsay, J., Yang, F.: You are what you tweet: personality expression and perception on Twitter. J. Res. Pers. 46(6), 710–718 (2012)
Azucar, D., Marengo, D., Settanni, M.: Predicting the Big 5 personality traits from digital footprints on social media: a meta-analysis. Pers. Individ. Differ. 124, 150–159 (2018)
Sterrett, D., Malato, D., Benz, J., Kantor, L., Tompson, T., Rosenstiel, T., Sonderman, J., Loker, K.: Who shared it?: deciding what news to trust on social media. Digit. Journal. 7(6), 783–801 (2019)
Golbeck, J., Robles, C., Turner, K.: Predicting personality with social media. In: CHI 2011 Extended Abstracts on Human Factors in Computing Systems (2011)
Goodman, L.A.: Snowball sampling. Ann. Math. Stat. 32(1), 148–170 (1961)
Nisbett, R.E., Wilson, T.D.: The halo effect: evidence for unconscious alteration of judgments. J. Pers. Soc. Psychol. 35(4), 250–256 (1977)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Ives-Keeler, C., Buckley, O., Lines, J. (2021). Understanding Trust in Social Media: Twitter. In: Stephanidis, C., Antona, M., Ntoa, S. (eds) HCI International 2021 - Posters. HCII 2021. Communications in Computer and Information Science, vol 1419. Springer, Cham. https://doi.org/10.1007/978-3-030-78635-9_57
Download citation
DOI: https://doi.org/10.1007/978-3-030-78635-9_57
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-78634-2
Online ISBN: 978-3-030-78635-9
eBook Packages: Computer ScienceComputer Science (R0)