Credibility by automation: Expectations of future knowledge production in social media analytics

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorPääkkönen, Juhoen_US
dc.contributor.authorLaaksonen, Salla Maariaen_US
dc.contributor.authorJauho, Mikkoen_US
dc.contributor.departmentDepartment of Computer Scienceen
dc.contributor.organizationDepartment of Computer Scienceen_US
dc.contributor.organizationUniversity of Helsinkien_US
dc.date.accessioned2020-03-06T15:25:10Z
dc.date.available2020-03-06T15:25:10Z
dc.date.issued2020-08en_US
dc.description.abstractSocial media analytics is a burgeoning new field associated with high promises of societal relevance and business value but also methodological and practical problems. In this article, we build on the sociology of expectations literature and research on expertise in the interaction between humans and machines to examine how analysts and clients make their expectations about social media analytics credible in the face of recognized problems. To investigate how this happens in different contexts, we draw on thematic interviews with 10 social media analytics and client companies. In our material, social media analytics appears as a field facing both hopes and skepticism – toward data, analysis methods, or the users of analytics – from both the clients and the analysts. In this setting, the idea of automated analysis through algorithmic methods emerges as a central notion that lends credibility to expectations about social media analytics. Automation is thought to, first, extend and make expert interpretation of messy social media data more rigorous; second, eliminate subjective judgments from measurement on social media; and, third, allow for coordination of knowledge management inside organizations. Thus, ideas of automation importantly work to uphold the expectations of the value of analytics. Simultaneously, they shape what kinds of expertise, tools, and practices come to be involved in the future of analytics as knowledge production.en
dc.description.versionPeer revieweden
dc.format.extent18
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationPääkkönen, J, Laaksonen, S M & Jauho, M 2020, 'Credibility by automation : Expectations of future knowledge production in social media analytics', Convergence, vol. 26, no. 4, 1354856520901839, pp. 790-807. https://doi.org/10.1177/1354856520901839en
dc.identifier.doi10.1177/1354856520901839en_US
dc.identifier.issn1354-8565
dc.identifier.issn1748-7382
dc.identifier.otherPURE UUID: 3954ab6e-d45e-48ec-b56c-25c3df572912en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/3954ab6e-d45e-48ec-b56c-25c3df572912en_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85079127880&partnerID=8YFLogxK
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/53821877/P_kk_nen_Credibility.1354856520901839.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/43376
dc.identifier.urnURN:NBN:fi:aalto-202003062419
dc.language.isoenen
dc.publisherSage Publishing
dc.relation.ispartofseriesConvergenceen
dc.relation.ispartofseriesVolume 26, issue 4, pp. 790-807en
dc.rightsopenAccessen
dc.subject.keywordalgorithmic knowledge productionen_US
dc.subject.keywordAnalytics as businessen_US
dc.subject.keywordanalytics in client companiesen_US
dc.subject.keywordautomationen_US
dc.subject.keywordbig dataen_US
dc.subject.keywordcredibilityen_US
dc.subject.keyworddata analyticsen_US
dc.subject.keyworddata imaginaryen_US
dc.subject.keywordobjectivityen_US
dc.subject.keywordqualitative methodsen_US
dc.subject.keywordsocial media analyticsen_US
dc.subject.keywordsociology of expectationsen_US
dc.titleCredibility by automation: Expectations of future knowledge production in social media analyticsen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
dc.type.versionpublishedVersion

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