We are what we click

Understanding time and content-based habits of online news readers

Journal Article (2020)
Author(s)

Mykola Makhortykh (University of Bern)

Natali Helberger (Vrije Universiteit Amsterdam)

Jaron J. Harambam (Vrije Universiteit Amsterdam)

Dimitrios Bountouridis (TU Delft - Web Information Systems)

Research Group
Web Information Systems
Copyright
© 2020 Mykola Makhortykh, Natali Helberger, Jaron Harambam, D. Bountouridis
DOI related publication
https://doi.org/10.1177/1461444820933221
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 Mykola Makhortykh, Natali Helberger, Jaron Harambam, D. Bountouridis
Research Group
Web Information Systems
Issue number
9
Volume number
23 (2021)
Pages (from-to)
2773-2800
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Abstract

The article contributes both conceptually and methodologically to the study of online news consumption by introducing new approaches to measuring user information behaviour and proposing a typology of users based on their click behaviour. Using as a case study two online outlets of large national newspapers, it employs computational approaches to detect patterns in time- and content-based user interactions with news content based on clickstream data. The analysis of interactions detects several distinct timelines of news consumption and scrutinises how users switch between news topics during reading sessions. Using clustering analysis, the article then identifies several types of news readers (e.g. samplers, gourmets) and examines their news diets. The results point out the limited variation in topical composition of the news diets between different types of readers and the tendency of these diets to align with the news supply patterns (i.e. the average distribution of topics covered by the outlet).