Extracting usability and user experience information from online user reviews

Steffen Hedegaard, Jakob Grue Simonsen

70 Citationer (Scopus)

Abstract

Internet review sites allow consumers to write detailed reviews of products potentially containing information related to user experience (UX) and usability. Using 5198 sentences from 3492 online reviews of software and video games, we investigate the content of online reviews with the aims of (i) charting the distribution of information in reviews among different dimensions of usability and UX, and (ii) extracting an associated vocabulary for each dimension using techniques from natural language processing and machine learning. We (a) find that 13%-49% of sentences in our online reviews pool contain usability or UX information; (b) chart the distribution of four sets of dimensions of usability and UX across reviews from two product categories; (c) extract a catalogue of important word stems for a number of dimensions. Our results suggest that a greater understanding of users' preoccupation with different dimensions of usability and UX may be inferred from the large volume of self-reported experiences online, and that research focused on identifying pertinent dimensions of usability and UX may benefit further from empirical studies of user-generated experience reports.

OriginalsprogEngelsk
TitelProceedings of the SIGCHI Conference on Human Factors in Computing Systems : CHI '13
Antal sider10
ForlagAssociation for Computing Machinery
Publikationsdato2013
Sider2089-2098
ISBN (Trykt)978-1-4503-1899-0
DOI
StatusUdgivet - 2013
BegivenhedThe ACM SIGCHI Conference on Human Factors in Computing Systems - Paris, Frankrig
Varighed: 27 apr. 20132 maj 2013

Konference

KonferenceThe ACM SIGCHI Conference on Human Factors in Computing Systems
Land/OmrådeFrankrig
ByParis
Periode27/04/201302/05/2013

Emneord

  • end user reviews, machine learning, natural language processing, usability, user experience

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