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Swipe and tell: Using implicit feedback to predict user engagement on tablets

Swipe and tell: Using implicit feedback to predict user engagement on tablets
Swipe and tell: Using implicit feedback to predict user engagement on tablets

When content consumers explicitly judge content positively, we consider them to be engaged. Unfortunately, explicit user evaluations are difficult to collect, as they require user effort. Therefore, we propose to use device interactions as implicit feedback to detect engagement. We assess the usefulness of swipe interactions on tablets for predicting engagement and make the comparison with using traditional features based on time spent. We gathered two unique datasets of more than 250,000 swipes, 100,000 unique article visits, and over 35,000 explicitly judged news articles by modifying two commonly used tablet apps of two newspapers. We tracked all device interactions of 407 experiment participants during one month of habitual news reading. We employed a behavioral metric as a proxy for engagement, because our analysis needed to be scalable to many users, and scanning behavior required us to allow users to indicate engagement quickly. We point out the importance of taking into account content ordering, report the most predictive features, zoom in on briefly read content and on the most frequently read articles. Our findings demonstrate that fine-grained tablet interactions are useful indicators of engagement for newsreaders on tablets. The best features successfully combine both time-based aspects and swipe interactions.

Briefly read content, Content ordering, Dwell time, Frequently read content, Implicit feedback, Newspaper, Online news, Tablets, Touch interactions, User engagement
1046-8188
Nelissen, Klaas
7427927d-66f5-49d8-88cb-0970f3364f26
Snoeck, Monique
9aee96bc-8a57-4c37-bcd7-e83f0b173ee1
Vanden Broucke, Seppe
89c69367-232e-4c1e-9e57-531bf474e12d
Baesens, Bart
f7c6496b-aa7f-4026-8616-ca61d9e216f0
Nelissen, Klaas
7427927d-66f5-49d8-88cb-0970f3364f26
Snoeck, Monique
9aee96bc-8a57-4c37-bcd7-e83f0b173ee1
Vanden Broucke, Seppe
89c69367-232e-4c1e-9e57-531bf474e12d
Baesens, Bart
f7c6496b-aa7f-4026-8616-ca61d9e216f0

Nelissen, Klaas, Snoeck, Monique, Vanden Broucke, Seppe and Baesens, Bart (2018) Swipe and tell: Using implicit feedback to predict user engagement on tablets. ACM Transactions on Information Systems, 36 (4), [35]. (doi:10.1145/3185153).

Record type: Article

Abstract

When content consumers explicitly judge content positively, we consider them to be engaged. Unfortunately, explicit user evaluations are difficult to collect, as they require user effort. Therefore, we propose to use device interactions as implicit feedback to detect engagement. We assess the usefulness of swipe interactions on tablets for predicting engagement and make the comparison with using traditional features based on time spent. We gathered two unique datasets of more than 250,000 swipes, 100,000 unique article visits, and over 35,000 explicitly judged news articles by modifying two commonly used tablet apps of two newspapers. We tracked all device interactions of 407 experiment participants during one month of habitual news reading. We employed a behavioral metric as a proxy for engagement, because our analysis needed to be scalable to many users, and scanning behavior required us to allow users to indicate engagement quickly. We point out the importance of taking into account content ordering, report the most predictive features, zoom in on briefly read content and on the most frequently read articles. Our findings demonstrate that fine-grained tablet interactions are useful indicators of engagement for newsreaders on tablets. The best features successfully combine both time-based aspects and swipe interactions.

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swipe-and-tell-ACM-TOIS - Accepted Manuscript
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More information

Accepted/In Press date: 1 February 2018
e-pub ahead of print date: 1 April 2018
Published date: 10 October 2018
Keywords: Briefly read content, Content ordering, Dwell time, Frequently read content, Implicit feedback, Newspaper, Online news, Tablets, Touch interactions, User engagement

Identifiers

Local EPrints ID: 425307
URI: http://eprints.soton.ac.uk/id/eprint/425307
ISSN: 1046-8188
PURE UUID: b6dbf612-3165-47a5-b443-949b3cdeb236
ORCID for Bart Baesens: ORCID iD orcid.org/0000-0002-5831-5668

Catalogue record

Date deposited: 12 Oct 2018 16:30
Last modified: 28 Apr 2022 01:53

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Contributors

Author: Klaas Nelissen
Author: Monique Snoeck
Author: Seppe Vanden Broucke
Author: Bart Baesens ORCID iD

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