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Can Humans Detect the Authenticity of Social Media Accounts?

Sandy, Christopher, Rusconi, Patrice and Li, Shujun (2017) Can Humans Detect the Authenticity of Social Media Accounts? In: 3rd IEEE International Conference on Cybernetics (CYBCONF-2017), 21-23 Jun 2017, Exeter, UK.

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Abstract

This study investigates the influence of verbal and non-verbal cues on people’s credibility judgments of fake Twitter profiles generated by an information hiding mobile app solely for transmitting secret messages. We tested the hypotheses that the trustworthiness conveyed by the profile picture, morality-related trait adjectives included in the profile summary and the profile owner’s gender would increase people’s credibility judgments of those fake Twitter profiles. 24 participants assessed 16 fake profiles on their credibility. They also expressed their confidence in their credibility judgements and they answered an open-ended question on which parts of the profile influenced their credibility judgements. The results showed that overall participants did not trust the Twitter profiles. Furthermore, confidence judgements were higher when profiles included competence-related traits in the profile summaries. Verbal rather than non-verbal cues had thus more influence on participants’ judgements. The openended responses revealed a large reliance on the content of the profile, which is what the mobile app relies on. We discussed these findings in light of the relative lack of credibility of the profiles generated by the mobile app. The new insights can help improve designs of systems depending on automated social media accounts and will provide useful clues about other applications where cognitive computing plays a role.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Computing Science
Authors :
NameEmailORCID
Sandy, ChristopherUNSPECIFIEDUNSPECIFIED
Rusconi, Patricep.rusconi@surrey.ac.ukUNSPECIFIED
Li, Shujunshujun.li@surrey.ac.ukUNSPECIFIED
Date : 21 June 2017
Funders : Engineering and Physical Sciences Research Council (EPSRC)
Copyright Disclaimer : © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords : Twitter; Social media; Twitterbots; Information Hiding; Mobile computing; Credibility; Confidence; Morality; Competence; Cognitive computing
Depositing User : Clive Harris
Date Deposited : 06 Jun 2017 13:02
Last Modified : 06 Jun 2017 14:52
URI: http://epubs.surrey.ac.uk/id/eprint/841313

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