Gaming Algorithmic Hate-Speech Detection: Stakes, Parties, and Moves

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorHaapoja, Jesseen_US
dc.contributor.authorLaaksonen, Salla-Maariaen_US
dc.contributor.authorLampinen, Airien_US
dc.contributor.departmentDepartment of Computer Scienceen
dc.contributor.groupauthorGroup Turpeinen M.en
dc.contributor.groupauthorHelsinki Institute for Information Technology (HIIT)en
dc.contributor.organizationUniversity of Helsinkien_US
dc.contributor.organizationStockholm Universityen_US
dc.date.accessioned2020-07-03T11:07:49Z
dc.date.available2020-07-03T11:07:49Z
dc.date.issued2020-04en_US
dc.description.abstractA recent strand of research considers how algorithmic systems are gamed in everyday encounters. We add to this literature with a study that uses the game metaphor to examine a project where different organizations came together to create and deploy a machine learning model to detect hate speech from political candidates' social media messages during the Finnish 2017 municipal election. Using interviews and forum discussions as our primary research material, we illustrate how the unfolding game is played out on different levels in a multi-stakeholder situation, what roles different participants have in the game, and how strategies of gaming the model revolve around controlling the information available to it. We discuss strategies that different stakeholders planned or used to resist the model, and show how the game is not only played against the model itself, but also with those who have created it and those who oppose it. Our findings illustrate that while “gaming the system” is an important part of gaming with algorithms, these games have other levels where humans play against each other, rather than against technology. We also draw attention to how deploying a hate-speech detection algorithm can be understood as an effort to not only detect but also preempt unwanted behavior.en
dc.description.versionPeer revieweden
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationHaapoja, J, Laaksonen, S-M & Lampinen, A 2020, ' Gaming Algorithmic Hate-Speech Detection: Stakes, Parties, and Moves ', Social Media + Society, vol. 6, no. 2, 924778 . https://doi.org/10.1177/2056305120924778en
dc.identifier.doi10.1177/2056305120924778en_US
dc.identifier.issn2056-3051
dc.identifier.otherPURE UUID: bbe61a73-12a3-42ab-b150-cbd4e4282a26en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/bbe61a73-12a3-42ab-b150-cbd4e4282a26en_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85087059042&partnerID=8YFLogxKen_US
dc.identifier.otherPURE LINK: https://doi.org/10.1177/2056305120924778en_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/43911078/2056305120924778.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/45329
dc.identifier.urnURN:NBN:fi:aalto-202007034286
dc.language.isoenen
dc.publisherSAGE Publications Ltd
dc.relation.ispartofseriesSocial Media + Societyen
dc.relation.ispartofseriesVolume 6, issue 2en
dc.rightsopenAccessen
dc.titleGaming Algorithmic Hate-Speech Detection: Stakes, Parties, and Movesen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
dc.type.versionpublishedVersion

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