Interest as a Proxy of Engagement in News Reading: Spectral and Entropy Analyses of EEG Activity Patterns

Ioannis Arapakis, Miguel Barreda-Angeles, Alexandre Pereda-Banos

Research output: Contribution to JournalArticleAcademicpeer-review


Objective measurements of engagement are increasingly sought after by both the media industry and scholar communities to explain what drives people to consume audiovisual contents. However, engagement is a complex construct that, at the psychological level, has been mainly operationalised through indicators of attentional and emotional processes, often overlooking motivational factors. We claim that in the context of news consumption, motivation, operationalised as intrinsic interest for consuming a given content, needs to be factored in together with attentional and emotional processes. The present work provides an objective metric for motivation based on electroencephalographic (EEG) registration of users' neural activity, while they read sets of news pre-classified in terms of their potential interest. We focus on a metric that has been used as an indicator of the degree to which an item or event induces the motivation to approach or escape, the so called frontal alpha asymmetry (FAA). Moreover, in addition to the traditional approach to the analysis of EEG signals, we also introduce a more novel technique based on estimating the entropy of the signals. Results confirm that FAA is indeed a good proxy for objective monitoring of interest in media contents and that entropy analysis, although its interpretation in terms of information processing warrants further investigation, is also sensitive to the manipulation of interest, providing results that complement traditional power spectrum analysis.

Original languageEnglish
Article number7878633
Pages (from-to)100-114
Number of pages15
JournalIEEE Transactions on Affective Computing
Issue number1
Publication statusPublished - 1 Jan 2019
Externally publishedYes


  • EEG
  • entropy analysis
  • news consumption
  • predictive modelling
  • spectral analysis
  • User engagement

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