Thick-Big Descriptions

Research output: Contribution to conferenceConference abstract for conferenceResearchpeer-review

The paper discusses the rewards and challenges of employing commercial audience measurements data – gathered by media industries for profitmaking purposes – in ethnographic research on the Internet in everyday life. It questions claims to the objectivity of big data (Anderson 2008), the assumption that bigger is always better, and the many legacy decisions and rules that ultimately govern how audiences are ‘made’ in commercial measurement companies. As such, the paper extends the discussions of a previous empirical study (Lai 2016) on how media organizations imagine their audiences (Ang 1991; Napoli 2010; Webster 2014). This study evolved around industry stakeholders resisting and negotiating changes, as they are happening, in media consumption dynamics and measurement standards, which inevitably reconceptualize future institutionally effective audiences (Ettema & Whitney 1994). With digital communication systems, language and behavior appear as texts, outputs, and discourses (data to be ‘found’) – big data then documents things that in earlier research required interviews and observations (data to be ‘made’) (Jensen 2014). However, web-measurement enterprises build audiences according to a commercial logic (boyd & Crawford 2011) and is as such directed by motives that call for specific types of sellable user data and specific segmentation strategies. In combining big data and ‘thick descriptions’ (Geertz 1973) scholars need to question how ethnographic fieldwork might map the ‘data not seen’ (Baym 2013) in big data, and how web-measurement practices expose significant cultural and political aspects of the contexts they operate in.
Original languageDanish
Publication date29 Sep 2017
Number of pages1
Publication statusPublished - 29 Sep 2017
EventAudiences 2030: Imagining a future for audiences - UNIVERSIDADE CATOLICA PORTUGUESA LISBOA, Lissabon, Portugal
Duration: 28 Sep 201729 Sep 2017


ConferenceAudiences 2030
Internet address

    Research areas

  • Faculty of Humanities - audience studies, audiences, audience measurement, big data, Ethnographic method, ethnography

ID: 178881941