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

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Social 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 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.
Original languageEnglish
Article number1354856520901839
JournalConvergence
Volume26
Issue number4
Pages (from-to)790-807
Number of pages18
ISSN1354-8565
DOIs
Publication statusPublished - 1 Aug 2020
MoE publication typeA1 Journal article-refereed

Fields of Science

  • 518 Media and communications
  • Analytics as business
  • analytics in client companies
  • algorithmic knowledge production
  • automation
  • big data
  • credibility
  • data analytics
  • data imaginary
  • objectivity
  • qualitative methods
  • social media analytics
  • sociology of expectations
  • BIG DATA
  • SOCIOLOGY
  • SCIENCE

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