FMC research process seminar this Tuesday. Exploring the ‘black box’ of Google News algorithms: a methodology

You are warmly invited to this week’s FMC research process seminar.

Tuesday 16 November, 2-3pm.

Exploring the ‘black box’ of Google News algorithms: a methodology

Prof Dan Jackson (BU)

The algorithms underpinning search results and recommendations – the cornerstone of navigating the web – have been described as “the great ‘known unknown’ of search engines” (Ørmen 2016, p.110). At the same time, news consumers are increasingly reliant on algorithms to sort, organise, and recommend news to us based on information that they collect from us. Given the normative implications of such a role, it’s therefore crucial we research the outcomes of algorithmic personalisation, especially in news. Methodologically, this is not a straightforward task, though, and one that communication scholars are still coming to terms with. In this presentation I will walk through the mixed methods research design employed in our study of news personalisation in Google News. First, in a quasi-experimental design, we asked a diverse set of participants to search Google News for four search terms and report the first five stories they were recommended on each term.  We then conducted a manual content analysis on the stories recommended by Google News for our search terms (N=192), focusing on their favourability towards the search term in question. After briefly summarising the outcomes of the study, I will then reflect on these methods and how we might apply them elsewhere.

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Meeting ID: 929 210 3478

Passcode: rps!4fmc