Skip to main content

Understanding Trust in Social Media: Twitter

Part of the Communications in Computer and Information Science book series (CCIS,volume 1419)


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 ( 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.


  • Trust
  • Misinformation
  • Twitter

This is a preview of subscription content, access via your institution.

Buying options

USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
USD   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions


  1. 1.


  1. 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)

    Google Scholar 

  2. 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).

    CrossRef  Google Scholar 

  3. 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)

    Google Scholar 

  4. 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)

    Google Scholar 

  5. 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)

    Google Scholar 

  6. Golbeck, J., Robles, C., Turner, K.: Predicting personality with social media. In: CHI 2011 Extended Abstracts on Human Factors in Computing Systems (2011)

    Google Scholar 

  7. Goodman, L.A.: Snowball sampling. Ann. Math. Stat. 32(1), 148–170 (1961)

    CrossRef  MathSciNet  Google Scholar 

  8. Nisbett, R.E., Wilson, T.D.: The halo effect: evidence for unconscious alteration of judgments. J. Pers. Soc. Psychol. 35(4), 250–256 (1977)

    CrossRef  Google Scholar 

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Catherine Ives-Keeler .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

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.

Download citation

  • DOI:

  • 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)