An empirical evaluation of the User Engagement Scale (UES) in online news environments

2015 ◽  
Vol 51 (4) ◽  
pp. 413-427 ◽  
Author(s):  
Heather O’Brien ◽  
Paul Cairns
Keyword(s):  
Empirical Evaluation ◽  
Online News ◽  
User Engagement ◽  
Engagement Scale

scholarly journals Content analytics based on random forest classification technique: An empirical evaluation using online news dataset

2021 ◽  
Vol 8 (2) ◽  
pp. 77-84
Author(s):  
Nohuddin et al. ◽  
Keyword(s):  
Random Forest ◽  
Empirical Evaluation ◽  
Online News ◽  
Document Management ◽  
Random Forest Algorithm ◽  
Random Forest Classification ◽  
Classification Technique ◽  
Forest Classification ◽  
Management Procedures ◽  
Text Content

In this paper, a study is established for exploiting a document classification technique for categorizing a set of random online documents. The technique is aimed to assign one or more classes or categories to a document, making it easier to manage and sort. This paper describes an experiment on the proposed method for classifying documents effectively using the decision tree technique. The proposed research framework is a Document Analysis based on the Random Forest Algorithm (DARFA). The proposed framework consists of 5 components, which are (i) Document dataset, (ii) Data Preprocessing, (iii) Document Term Matrix, (iv) Random Forest classification, and (v) Visualization. The proposed classification method can analyze the content of document datasets and classifies documents according to the text content. The proposed framework use algorithms that include TF-IDF and Random Forest algorithm. The outcome of this study benefits as an enhancement to document management procedures like managing documents in daily business operations, consolidating inventory systems, organizing files in databases, and categorizing document folders.

scholarly journals Applicability of the User Engagement Scale to Mobile Health: A Survey-Based Quantitative Study

10.2196/13244 ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. e13244 ◽  
Author(s):  
Marianne Holdener ◽  
Alain Gut ◽  
Alfred Angerer
Keyword(s):  
Mobile Health ◽  
Mobile Apps ◽  
Principal Component ◽  
Focused Attention ◽  
User Engagement ◽  
Aesthetic Appeal ◽  
Health Apps ◽  
Perceived Usability ◽  
Sum Scores ◽  
Engagement Scale

Background There has recently been exponential growth in the development and use of health apps on mobile phones. As with most mobile apps, however, the majority of users abandon them quickly and after minimal use. One of the most critical factors for the success of a health app is how to support users’ commitment to their health. Despite increased interest from researchers in mobile health, few studies have examined the measurement of user engagement with health apps. Objective User engagement is a multidimensional, complex phenomenon. The aim of this study was to understand the concept of user engagement and, in particular, to demonstrate the applicability of a user engagement scale (UES) to mobile health apps. Methods To determine the measurability of user engagement in a mobile health context, a UES was employed, which is a psychometric tool to measure user engagement with a digital system. This was adapted to Ada, developed by Ada Health, an artificial intelligence–powered personalized health guide that helps people understand their health. A principal component analysis (PCA) with varimax rotation was conducted on 30 items. In addition, sum scores as means of each subscale were calculated. Results Survey data from 73 Ada users were analyzed. PCA was determined to be suitable, as verified by the sampling adequacy of Kaiser-Meyer-Olkin=0.858, a significant Bartlett test of sphericity (χ2300=1127.1; P<.001), and communalities mostly within the 0.7 range. Although 5 items had to be removed because of low factor loadings, the results of the remaining 25 items revealed 4 attributes: perceived usability, aesthetic appeal, reward, and focused attention. Ada users showed the highest engagement level with perceived usability, with a value of 294, followed by aesthetic appeal, reward, and focused attention. Conclusions Although the UES was deployed in German and adapted to another digital domain, PCA yielded consistent subscales and a 4-factor structure. This indicates that user engagement with health apps can be assessed with the German version of the UES. These results can benefit related mobile health app engagement research and may be of importance to marketers and app developers.

User Engagement Scale--Short Form

2018 ◽  
Author(s):  
Heather L. O'Brien ◽  
Paul Cairns ◽  
Mark Hall
Keyword(s):  
Short Form ◽  
User Engagement ◽  
Engagement Scale

Measuring engagement in video game-based environments: Investigation of the User Engagement Scale

2014 ◽  
Vol 32 ◽  
pp. 123-132 ◽  
Author(s):  
Eric N. Wiebe ◽  
Allison Lamb ◽  
Megan Hardy ◽  
David Sharek
Keyword(s):  
Video Game ◽  
User Engagement ◽  
Engagement Scale

scholarly journals Applicability of the User Engagement Scale to Mobile Health: A Survey-Based Quantitative Study (Preprint)

2018 ◽  
Author(s):  
Marianne Holdener ◽  
Alain Gut ◽  
Alfred Angerer
Keyword(s):  
Mobile Health ◽  
Mobile Apps ◽  
Principal Component ◽  
Focused Attention ◽  
User Engagement ◽  
Aesthetic Appeal ◽  
Health Apps ◽  
Perceived Usability ◽  
Sum Scores ◽  
Engagement Scale

BACKGROUND There has recently been exponential growth in the development and use of health apps on mobile phones. As with most mobile apps, however, the majority of users abandon them quickly and after minimal use. One of the most critical factors for the success of a health app is how to support users’ commitment to their health. Despite increased interest from researchers in mobile health, few studies have examined the measurement of user engagement with health apps. OBJECTIVE User engagement is a multidimensional, complex phenomenon. The aim of this study was to understand the concept of user engagement and, in particular, to demonstrate the applicability of a user engagement scale (UES) to mobile health apps. METHODS To determine the measurability of user engagement in a mobile health context, a UES was employed, which is a psychometric tool to measure user engagement with a digital system. This was adapted to Ada, developed by Ada Health, an artificial intelligence–powered personalized health guide that helps people understand their health. A principal component analysis (PCA) with varimax rotation was conducted on 30 items. In addition, sum scores as means of each subscale were calculated. RESULTS Survey data from 73 Ada users were analyzed. PCA was determined to be suitable, as verified by the sampling adequacy of Kaiser-Meyer-Olkin=0.858, a significant Bartlett test of sphericity (χ<sup>2</sup><sub>300</sub>=1127.1; <italic>P</italic>&lt;.001), and communalities mostly within the 0.7 range. Although 5 items had to be removed because of low factor loadings, the results of the remaining 25 items revealed 4 attributes: perceived usability, aesthetic appeal, reward, and focused attention. Ada users showed the highest engagement level with perceived usability, with a value of 294, followed by aesthetic appeal, reward, and focused attention. CONCLUSIONS Although the UES was deployed in German and adapted to another digital domain, PCA yielded consistent subscales and a 4-factor structure. This indicates that user engagement with health apps can be assessed with the German version of the UES. These results can benefit related mobile health app engagement research and may be of importance to marketers and app developers.

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