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Do players communicate differently depending on the champion played? Exploring the Proteus effect in League of Legends

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  • Şengün, Sercan
  • Santos, Joao M.
  • Salminen, Joni
  • Jung, Soon-gyo
  • Jansen, Bernard J.

Abstract

We investigate how the Proteus effect, which is players changing their way of communication based on characters with which they play, is associated with players’ champion usage in the popular online game League of Legends, where champions are the characters that the players control. First, we create two sets of variables: (a) objective champion characteristics based on information from the game developer, which we further enrich by semiotic coding, and (b) subjective champion characteristics based on crowdsourced opinions about the champions. Then, we analyze 13.6 million in-game chat messages to measure whether the players’ vocality (character counts of messages), valence (negative versus positive scores of language use), and toxicity (frequency of toxic word usage) change depending on the characteristics of the champions they employ. We find that champions’ body type, role, and gender are associated with players’ higher vocality, toxicity, and negative valence. We also find that the players’ communication significantly changes in toxicity and valence when they play using different champions. We discuss our methodology and results in detail and propose design directions and other implications based on them.

Suggested Citation

  • Şengün, Sercan & Santos, Joao M. & Salminen, Joni & Jung, Soon-gyo & Jansen, Bernard J., 2022. "Do players communicate differently depending on the champion played? Exploring the Proteus effect in League of Legends," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    • Handle: RePEc:eee:tefoso:v:177:y:2022:i:c:s0040162522000889
    DOI: 10.1016/j.techfore.2022.121556
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    References listed on IDEAS

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    1. Xanthopoulou, Despoina & Papagiannidis, Savvas, 2012. "Play online, work better? Examining the spillover of active learning and transformational leadership," Technological Forecasting and Social Change, Elsevier, vol. 79(7), pages 1328-1339.
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    3. Christine Abdalla Mikhaeil & Richard Baskerville, 2019. "Using semiotics to analyze representational complexity in social media," Post-Print hal-02509212, HAL.
    4. Brendan Maher, 2016. "Can a video game company tame toxic behaviour?," Nature, Nature, vol. 531(7596), pages 568-571, March.
    5. Panourgias, Nikiforos S. & Nandhakumar, Joe & Scarbrough, Harry, 2014. "Entanglements of creative agency and digital technology: A sociomaterial study of computer game development," Technological Forecasting and Social Change, Elsevier, vol. 83(C), pages 111-126.
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    Cited by:

    1. Xiang, Diandian & Li, Xia & Hampson, Daniel Peter, 2023. "Service exchange activities in the sharing economy: Professional versus amateur peer providers," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    2. Şengün, Sercan & Mawhorter, Peter & Bowie-Wilson, James & Audeh, Yusef & Kwak, Haewoon & Harrell, D. Fox, 2022. "Contours of virtual enfreakment in fighting game characters," Technological Forecasting and Social Change, Elsevier, vol. 180(C).

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