Considering the Elaboration Likelihood Model for simulating hate and counter speech on Facebook

Carla Schieb; Mike Preuss

doi:10.5771/2192-4007-2018-4-580

Contents
- Chapter Expand | CollapseAuthorsPage
- I–II Titelei/Inhaltsverzeichnis I–II
- 459–472 EDITORIAL 459–472
  - Hate and counter-voices in the Internet: Introduction to the special issue Diana Rieger, Josephine B. Schmitt, Lena Frischlich Diana Rieger, Josephine B. Schmitt, Lena Frischlich
- 473–606 FULL PAPER 473–606
  - 473–498 Can it be hate if it is fun? Discursive ensembles of hatred and laughter in extreme right satire on Facebook Christian Schwarzenegger, Anna Wagner Christian Schwarzenegger, Anna Wagner 473–498
  - 499–524 Journalists as targets of hate speech. How German journalists perceive the consequences for themselves and how they cope with it Magdalena Obermaier, Michaela Hofbauer, Carsten Reinemann Magdalena Obermaier, Michaela Hofbauer, Carsten Reinemann 499–524
  - 525–554 Journalistic counter-voices in comment sections: Patterns, determinants, and potential consequences of interactive moderation of uncivil user comments Marc Ziegele, Pablo Jost, Marike Bormann, Dominique Heinbach Marc Ziegele, Pablo Jost, Marike Bormann, Dominique Heinbach 525–554
  - 555–579 Perceiving threat and feeling responsible. How severity of hate speech, number of bystanders, and prior reactions of others affect bystanders’ intention to counterargue against hate speech on Facebook Larissa Leonhard, Christina Rueß, Magdalena Obermaier, Carsten Reinemann Larissa Leonhard, Christina Rueß, Magdalena Obermaier, Carsten Reinemann 555–579
  - 580–606 Considering the Elaboration Likelihood Model for simulating hate and counter speech on Facebook Carla Schieb, Mike Preuss Carla Schieb, Mike Preuss 580–606
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SCM Studies in Communication and Media , page 580 - 606

Considering the Elaboration Likelihood Model for simulating hate and counter speech on Facebook

Autoren

Carla Schieb Mike Preuss

DOI
- doi.org/10.5771/2192-4007-2018-4-580
- ISSN online: 2192-4007
Abstract

Counter speech is perceived and has also been advocated by social networks as a measure for delimiting the effects of hate speech. To facilitate estimating the efficiency of counter speech in freely accessible blackboard communication as employed by Facebook, we extend an existing simulation model by integrating Elaboration Likelihood Model (ELM) mechanisms. We model four different user groups (core, clowns, followers and counter speakers), each with a specific set of properties, namely need for cognition and involvement as ELM personal characteristics, and opinion, volatility and activity as borrowed from opinion formation models. We also add argument strength as important message characteristic. Our simulation experiments show that the updated model provides similar but much more detailed results: potentially temporal opinion changes via peripheral processing get visible. Furthermore, we give more evidence that the opinions of counter speakers shall not be too extreme in all cases but sometimes rather moderate in order to achieve maximum impact.
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