Linking media content and survey data in a dynamic and digital media environment – mobile longitudinal linkage analysis

Open Access
Authors
Publication date 2022
Journal Digital Journalism
Volume | Issue number 10 | 1
Pages (from-to) 200-215
Number of pages 16
Organisations
  • Faculty of Social and Behavioural Sciences (FMG) - Amsterdam School of Communication Research (ASCoR)
  • Faculty of Social and Behavioural Sciences (FMG)
Abstract
We introduce a design that is able to face some of the challenges that digital news consumption is posing to traditional media effects methods like linkage analysis. The challenges include (1) memory errors and biases when reporting everyday news media consumption leading to (2) errors when linking mass media outlets to survey data; (3) personalization of media content, as well as (4) short-term dynamic processes. Mobile Intensive Longitudinal Linkage Analysis (MILLA) uses an innovative combination of smartphone data donations to capture media exposure and relevant media content, a mobile experience sampling questionnaire to capture immediate reactions to news, and the content analysis of uploaded news media content to measure media effects. The design is explained by using an example of negativity in the news and its effects on emotional reactions of recipients.
Document type Article
Language English
Published at https://doi.org/10.1080/21670811.2021.1890169
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