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Article published In: Register and social media
Edited by Isobelle Clarke and Jack Grieve
[Register Studies 4:2] 2022
► pp. 202–231

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Same person, different platform

Challenges and implications for forensic authorship analysis. An exploratory study of Instagram and Twitter users

ORCiD logo with link | University of Graz
 | University of Graz
 | University of Graz
Published online: 6 October 2022
DOI logo with link
https://doi.org/10.1075/rs.22006.mar
Abstract
The importance of digital data in forensic contexts has been increasing continuously (e.g., Grant, T. (2013). Txt 4n6: Method, consistency, and distinctiveness in the analysis of SMS text messages. Journal of Law and Policy, 21(2), 467–494.Google Scholar logo with link to Google Scholar; Layton, R., Watters, P., & Dazeley, R. (2010). Authorship attribution for Twitter in 140 characters or less. IEEEI, 1–8. Google Scholar logo with link to Google Scholar; Wright, D. (2013). Stylistic variation within genre conventions in the Enron email corpus. The International Journal of Speech, Language and the Law, 20(1), 45–75. Google Scholar logo with link to Google Scholar), with individuals holding an average of 8.5 different social media accounts in 2018 (Statista (2021a). Average number of social media accounts per Internet user from 2013 to 2018. [URL]). Even though numerous studies have investigated registers on social media platforms (e.g., Seargeant, P., & Tagg, C. (2014). The language of social media. London: Palgrave Macmillan. Google Scholar logo with link to Google Scholar; Zappavigna, M. (2013). Discourse of Twitter and social media. London: Bloomsbury.Google Scholar logo with link to Google Scholar), it has rarely been attempted to describe individual styles of one and the same person on different platforms – a research gap this paper attempts to address with the help of an exploratory hypothesis-generating study. The data is drawn from Instagram and Twitter, and comprises 1,800 posts from three media representatives and/or writers that hold accounts with both platforms. The results of the analysis suggest that the use of some features (e.g., emoji, hashtags) is strongly influenced by the respective platforms, while other features (e.g., patterns of punctuation, use of types of speech acts) remain stable and thus offer promising avenues for authorship analysis.
Article outline
  • 1.Introduction
    • 1.1Approaches to researching online behavior: Computer-mediated discourse (CMD)
    • 1.2Registers of social media platforms
      • 1.2.1Twitter
      • 1.2.2Instagram
    • 1.3Forensic authorship analysis & individual styles
  • 2.Data
  • 3.Methodology
    • 3.1Genre, register, style
    • 3.2Ethical considerations
    • 3.3Limitations
  • 4.Analysis
    • 4.1Differences in individual style – Platform-dependent register
      • 4.1.1DS – Structural level (post-final periods)
      • 4.1.2OS – Level of meaning (interrogative speech acts)
      • 4.1.3MY – Level of interaction & discourse (@mentions)
    • 4.2Similarities in platform-independent individual style
      • 4.2.1DS – Structural level (missing hyphens)
      • 4.2.2MY – Level of meaning (commissive & directive speech acts)
      • 4.2.3OS – Level of interaction & discourse (emoji)
  • 5.Discussion
  • 6.Conclusions
  • Notes
  • References
References (106)
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