Inferring User Engagement from Interaction Data

Research output: Contribution to conferencePaper

Abstract

This paper presents preliminary results of a study designed to quantify users' engagement levels with interactive media content, through self-reported measures and interaction data. The broad hypothesis of the study is that interaction data can be used to predict the level of engagement felt by the user. The challenge addressed in this work is to explore the effectiveness of interaction data to act as a proxy for engagement levels and reveal what that data shows about engagement with media content. Preliminary results suggest several interesting insights about participants engagement and behaviour. Crucially, temporal statistics support the hypothesis that the participant making use of the controls in the interactive, video-based experience positively correlates with higher engagement.

Bibliographical metadata

Original languageEnglish
DOIs
Publication statusPublished - May 2019
EventACM 2019 CHI Conference on Human Factors in Computing Systems: Extended Abstracts - Glasgow, United Kingdom
Event duration: 4 May 20199 May 2019
https://dl.acm.org/citation.cfm?id=3290605

Conference

ConferenceACM 2019 CHI Conference on Human Factors in Computing Systems
Abbreviated titleCHI
CountryUnited Kingdom
CityGlasgow
Period4/05/199/05/19
Internet address