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The Digital Flynn Effect: Complexity of Posts on Social Media Increases over Time

Part of the Lecture Notes in Computer Science book series (LNISA,volume 10540)

Abstract

Parents and teachers often express concern about the extensive use of social media by youngsters. Some of them see emoticons, undecipherable initialisms and loose grammar typical for social media as evidence of language degradation. In this paper, we use a simple measure of text complexity to investigate how the complexity of public posts on a popular social networking site changes over time. We analyze a unique dataset that contains texts posted by 942, 336 users from a large European city across nine years. We show that the chosen complexity measure is correlated with the academic performance of users: users from high-performing schools produce more complex texts than users from low-performing schools. We also find that complexity of posts increases with age. Finally, we demonstrate that overall language complexity of posts on the social networking site is constantly increasing. We call this phenomenon the digital Flynn effect. Our results may suggest that the worries about language degradation are not warranted.

Keywords

  • Social media
  • Language complexity
  • Academic performance

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Correspondence to Ivan Smirnov .

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Smirnov, I. (2017). The Digital Flynn Effect: Complexity of Posts on Social Media Increases over Time. In: Ciampaglia, G., Mashhadi, A., Yasseri, T. (eds) Social Informatics. SocInfo 2017. Lecture Notes in Computer Science(), vol 10540. Springer, Cham. https://doi.org/10.1007/978-3-319-67256-4_3

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  • DOI: https://doi.org/10.1007/978-3-319-67256-4_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67255-7

  • Online ISBN: 978-3-319-67256-4

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