User Engagement – A Scientific Challenge

Author: Mounia Lalmas
Publication Date: 2012


In the online world, user engagement refers to the quality of the user experience that emphasizes the positive aspects of the interaction with technology and, in particular, the phenomena associated with wanting to use that technology longer and frequently. This definition is motivated by the observation that successful technologies are not just used, but they are engaged with. Engagement is measured in many ways, through self-report methods (e.g., questionnaires), observer methods (e.g., facial expression analysis, speech analysis, desktop actions, etc.), neuro-physiological signal processing methods (e.g., respiratory and cardiovascular accelerations and decelerations, muscle spasms, etc.), and from a web analytics perspective (through online behavior metrics that assess users’ depth of engagement with a site). However, little is known in validating and relating the measures coming from these various angles and so providing a firm basis for assessing the quality of the user experience, in terms of engagement. My goal is to address this problem by combining techniques from web analytics and existing works on user engagement coming from the domains of information science, multimodal human computer interaction and cognitive psychology.

This talk comprises three "inter-woven" parts: (1) I will define user engagement, list its many characteristics as identified in the research and analytic literature, and discuss the challenges associated with measuring user engagement. (2) I will describe data-driven approaches looking at user engagement through the development of new models and measures that allow for a better representation of how users engage within and across different web services. (3) I will describe how looking at affect and cognition are providing additional insights into measuring user engagement.



ACM COPYRIGHT NOTICE. Copyright © 2012 by the Association for Computing Machinery, Inc. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Publications Dept., ACM, Inc., fax +1 (212) 869-0481, or

Copyright © 2015 Yahoo. All rights reserved.