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Quantifying the Effects of Age-Related Stereotypes on Online Social Conformity

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Human-Computer Interaction – INTERACT 2021 (INTERACT 2021)

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Abstract

Social conformity is the act of individuals adjusting personal judgements to conform to expectations of opposing majorities in group settings. While conformity has been studied in online groups with emphasis on its contextual determinants (e.g., group size, social presence, task objectivity), the effect of age – of both the individual and the members of the opposing majority group – is yet to be thoroughly investigated. This study investigates differences in conformity behaviour in young adults (Generation Z) and middle-aged adults (Generation X) attempting an online group quiz containing stereotypically age-biased questions, when their personal responses are challenged by older and younger peers. Our results indicate the influence of age-related stereotypes on participants’ conformity behaviour with both young and middle-aged adults stereotypically perceiving the competency of their peers based on peer age. Specifically, participants were more inclined to conform to older majorities and younger majorities in quiz questions each age group was stereotypically perceived to be more knowledgeable about (1980’s history and social media & latest technology respectively). We discuss how our findings highlight the need to re-evaluate popular online user representations, to mitigate undesirable effects of age-related stereotypical perceptions leading to conformity.

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Authors and Affiliations

  1. The University of Melbourne, Melbourne, Australia

    Senuri Wijenayake, Jolan Hu, Vassilis Kostakos & Jorge Goncalves

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  1. Senuri Wijenayake
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  2. Jolan Hu
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  3. Vassilis Kostakos
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  4. Jorge Goncalves
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Correspondence to Senuri Wijenayake .

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Editors and Affiliations

  1. Department of Electrical and Information Engineering, Polytechnic University of Bari, Bari, Italy

    Carmelo Ardito

  2. Computer Science Department, University of Bari Aldo Moro, Bari, Italy

    Rosa Lanzilotti

  3. Computer Science Department, University of Pisa, Pisa, Italy

    Alessio Malizia

  4. Department of Computer Science, University of York, York, UK

    Helen Petrie

  5. Computer Science Department, University of Bari Aldo Moro, Bari, Italy

    Antonio Piccinno

  6. Computer Science Department, University of Bari Aldo Moro, Bari, Italy

    Giuseppe Desolda

  7. Microsoft Research, Redmond, WA, USA

    Kori Inkpen

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Wijenayake, S., Hu, J., Kostakos, V., Goncalves, J. (2021). Quantifying the Effects of Age-Related Stereotypes on Online Social Conformity. In: Ardito, C., et al. Human-Computer Interaction – INTERACT 2021. INTERACT 2021. Lecture Notes in Computer Science(), vol 12935. Springer, Cham. https://doi.org/10.1007/978-3-030-85610-6_26

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