Barral, Oswald and Eugster, Manuel J.A. and Ruotsalo, Tuukka and Spapé, Michiel M. and Kosunen, Ilkka and Ravaja, Niklas and Kaski, Samuel and Jacucci, Giulio (2016) Extracting Relevance and Affect Information from Physiological Text Annotation. User Modeling and User-Adapted Interaction: The Journal of Personalization Research, 26 (5). pp. 493-520. ISSN 0924-1868
This is the latest version of this item.
![]() |
Text (Last submitted version (LaTex))
Barral - Exploring.pdf - Accepted Version Download (1MB) |
Abstract
We present physiological text annotation, which refers to the practice of associating physiological responses to text content in order to infer characteristics of the user information needs and affective responses. Text annotation is a laborious task, and implicit feedback has been studied as a way to collect annotations without requiring any explicit action from the user. Previous work has explored behavioral signals, such as clicks or dwell time to automatically infer annotations, and physiological signals have mostly been explored for image or video content. We report on two experiments in which physiological text annotation is studied first to 1) indicate perceived relevance and then to 2) indicate affective responses of the users. The first experiment tackles the user’s perception of relevance of an information item, which is fundamental towards revealing the user’s information needs. The second experiment is then aimed at revealing the user’s affective responses towards a -relevant- text document. Results show that physiological user signals are associated with relevance and affect. In particular, electrodermal activity (EDA) was found to be different when users read relevant content than when they read irrelevant content and was found to be lower when reading texts with negative emotional content than when reading texts with neutral content. Together, the experiments show that physiological text annotation can provide valuable implicit inputs for personalized systems. We discuss how our findings help design personalized systems that can annotate digital content using human physiology without the need for any explicit user interaction.
Item Type: | Article |
---|---|
Additional Information and Comments: | The final publication is available at https://link.springer.com/article/10.1007/s11257-016-9184-8 |
Faculty / Department: | Faculty of Human and Digital Sciences > School of Psychology |
Depositing User: | Michiel Spape |
Date Deposited: | 21 Jun 2017 14:50 |
Last Modified: | 15 Nov 2017 01:15 |
URI: | https://hira.hope.ac.uk/id/eprint/2044 |
Available Versions of this Item
-
Exploring Peripheral Physiology as a Predictor of Perceived Relevance in Information Retrieval. (deposited 14 Dec 2016 15:45)
-
Exploring Peripheral Physiology as a Predictor of Perceived Relevance in Information Retrieval. (deposited 30 Aug 2017 08:29)
- Extracting Relevance and Affect Information from Physiological Text Annotation. (deposited 21 Jun 2017 14:50) [Currently Displayed]
-
Exploring Peripheral Physiology as a Predictor of Perceived Relevance in Information Retrieval. (deposited 30 Aug 2017 08:29)
Actions (login required)
![]() |
View Item |