License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.LDK.2021.39
URN: urn:nbn:de:0030-drops-145751
URL: https://drops.dagstuhl.de/opus/volltexte/2021/14575/
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Waterschoot, Cedric ; van den Bosch, Antal ; van den Hemel, Ernst

Calculating Argument Diversity in Online Threads

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OASIcs-LDK-2021-39.pdf (0.5 MB)


Abstract

We propose a method for estimating argument diversity and interactivity in online discussion threads. Using a case study on the subject of Black Pete ("Zwarte Piet") in the Netherlands, the approach for automatic detection of echo chambers is presented. Dynamic thread scoring calculates the status of the discussion on the thread level, while individual messages receive a contribution score reflecting the extent to which the post contributed to the overall interactivity in the thread. We obtain platform-specific results. Gab hosts only echo chambers, while the majority of Reddit threads are balanced in terms of perspectives. Twitter threads cover the whole spectrum of interactivity. While the results based on the case study mirror previous research, this calculation is only the first step towards better understanding and automatic detection of echo effects in online discussions.

BibTeX - Entry

@InProceedings{waterschoot_et_al:OASIcs.LDK.2021.39,
  author =	{Waterschoot, Cedric and van den Bosch, Antal and van den Hemel, Ernst},
  title =	{{Calculating Argument Diversity in Online Threads}},
  booktitle =	{3rd Conference on Language, Data and Knowledge (LDK 2021)},
  pages =	{39:1--39:9},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-199-3},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{93},
  editor =	{Gromann, Dagmar and S\'{e}rasset, Gilles and Declerck, Thierry and McCrae, John P. and Gracia, Jorge and Bosque-Gil, Julia and Bobillo, Fernando and Heinisch, Barbara},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2021/14575},
  URN =		{urn:nbn:de:0030-drops-145751},
  doi =		{10.4230/OASIcs.LDK.2021.39},
  annote =	{Keywords: Social Media, Echo Chamber, Interactivity, Argumentation, Stance}
}

Keywords: Social Media, Echo Chamber, Interactivity, Argumentation, Stance
Collection: 3rd Conference on Language, Data and Knowledge (LDK 2021)
Issue Date: 2021
Date of publication: 30.08.2021
Supplementary Material: Software (Source Code): https://github.com/Cwaterschoot/Interactivity_scoring archived at: https://archive.softwareheritage.org/swh:1:dir:f369c7b7343ace35ad1a916e37708dbae8dd3252


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