AUX and UX Evaluation of User Tools in Social Networks

Sánchez-Adame, Luis Martín; Mendoza, Sonia; González-Beltrán, Beatriz A.; Rodríguez, José; Viveros, Amilcar Meneses

doi:10.1109/wi.2018.0-101

Cited by 3 publications

(3 citation statements)

References 31 publications

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“…This paper gives continuity and expands the research that we have previously published on this topic [36,37]. The objective of the present work was to know whether there are and which are the differences between User eXpectations (AUX) and the experiences they find on social networks (EUX).…”

Section: Introductionmentioning

confidence: 56%

Measuring Anticipated and Episodic UX of Tasks in Social Networks

2020

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Today, social networks are crucial commodities that allow people to share different contents and opinions. In addition to participation, the information shared within social networks makes them attractive, but success is also accompanied by a positive User eXperience (UX). Social networks must offer useful and well-designed user-tools, i.e., sets of widgets that allow interaction among users. To satisfy this requirement, Episodic User eXperience (EUX) yields reactions of users after having interacted with an artifact. Anticipated User eXperience (AUX) grants the designers the capacity to recollect users’ aspirations, assumptions, and needs in the initial development phase of an artifact. In this work, we collect UX perceived in both periods to contrast user expectations and experiences offered on social networks, in order to find elements that could improve the design of user-tools. We arrange a test where participants (N=20) designed prototypes on paper to solve tasks and then did the same tasks on online social networks. Both stages are assessed with the help of AttrakDiff, and then we analyze the results through t-tests. The results we obtained suggest that users are inclined towards pragmatic aspects of their user-tools expectations.

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Section: Introductionmentioning

confidence: 56%

Measuring Anticipated and Episodic UX of Tasks in Social Networks

2020

Self Cite

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“…Other literature sources also concentrate on searching for and evaluating UX output heuristics. Authors in [15] state that "… in this article, we propose a novel AUX (Anticipated User eXperience) and UX evaluation method through which developers can obtain a knowledge base to create their designs… Intended Use: This criterion refers to the usage purpose of each user tool. For example, the way the user believes that a chat should work… Positive Anticipated Emotion: It concerns pleasant emotions that a user anticipates experiencing as a consequence of interacting with a user tool... ".…”

Section: Target Data Definition Based On Ux/cx Evaluation Heuristicsmentioning

confidence: 99%

Mapping of Source and Target Data for Application to Machine Learning Driven Discovery of IS Usability Problems

Nikiforova

Zabiniako

Kornienko

et al. 2021

Applied Computer Systems

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Improving IS (Information System) end-user experience is one of the most important tasks in the analysis of end-users behaviour, evaluation and identification of its improvement potential. However, the application of Machine Learning methods for the UX (User Experience) usability and effic iency improvement is not widely researched. In the context of the usability analysis, the information about behaviour of end-users could be used as an input, while in the output data the focus should be made on non-trivial or difficult attention-grabbing events and scenarios. The goal of this paper is to identify which data potentially can serve as an input for Machine Learning methods (and accordingly graph theory, transformation methods, etc.), to define dependency between these data and desired output, which can help to apply Machine Learning / graph algorithms to user activity records.

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“…Only two studies [8,36] use sensors, such as eye trackers, to identify the area that the user is observing. Almost half of the studies [1,2,8,32,33,[41][42][43][44][45][46] use some form of questionnaire to obtain qualitative information about user experience or usability. The vast majority of studies perform in loco evaluation, with the specialist observing the test in the same location as the participant, except for References [8,30,36], where the specialist remotely observe user interaction.…”

Section: Related Workmentioning

confidence: 99%

UXmood—A Sentiment Analysis and Information Visualization Tool to Support the Evaluation of Usability and User Experience

et al. 2019

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This paper presents UXmood, a tool that provides quantitative and qualitative information to assist researchers and practitioners in the evaluation of user experience and usability. The tool uses and combines data from video, audio, interaction logs and eye trackers, presenting them in a configurable dashboard on the web. The UXmood works analogously to a media player, in which evaluators can review the entire user interaction process, fast-forwarding irrelevant sections and rewinding specific interactions to repeat them if necessary. Besides, sentiment analysis techniques are applied to video, audio and transcribed text content to obtain insights on the user experience of participants. The main motivations to develop UXmood are to support joint analysis of usability and user experience, to use sentiment analysis for supporting qualitative analysis, to synchronize different types of data in the same dashboard and to allow the analysis of user interactions from any device with a web browser. We conducted a user study to assess the data communication efficiency of the visualizations, which provided insights on how to improve the dashboard.

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AUX and UX Evaluation of User Tools in Social Networks

Cited by 3 publications

References 31 publications

Measuring Anticipated and Episodic UX of Tasks in Social Networks

Measuring Anticipated and Episodic UX of Tasks in Social Networks

Mapping of Source and Target Data for Application to Machine Learning Driven Discovery of IS Usability Problems

UXmood—A Sentiment Analysis and Information Visualization Tool to Support the Evaluation of Usability and User Experience

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