Matching Items (4)
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- All Subjects: Mobile Applications
- Creators: D'Angelo, Barbara J.
- Creators: Lin, Elva
Description
This paper presents the results of an empirical analysis of deceptive data visualizations paired with explanatory text. Data visualizations are used to communicate information about important social issues to large audiences and are found in the news, social media, and the Internet (Kirk, 2012). Modern technology and software allow people and organizations to easily produce and publish data visualizations, contributing to data visualizations becoming more prevalent as a means of communicating important information (Sue & Griffin, 2016). Ethical transgressions in data visualizations are the intentional or unintentional use of deceptive techniques with the potential of altering the audience’s understanding of the information being presented (Pandey et al., 2015). While many have discussed the importance of ethics in data visualization, scientists have only recently started to look at how deceptive data visualizations affect the reader. This study was administered as an on-line user survey and was designed to test the deceptive potential of data visualizations when they are accompanied by a paragraph of text. The study consisted of a demographic questionnaire, chart familiarity assessment, and data visualization survey. A total of 256 participants completed the survey and were evenly distributed between a control (non-deceptive) survey or a test (deceptive) survey in which participant were asked to observe a paragraph of text and data visualization paired together. Participants then answered a question relevant to the observed information to measure how they perceived the information to be. The individual differences between demographic groups and their responses were analyzed to understand how these groups reacted to deceptive data visualizations compared to the control group. The results of the study confirmed that deceptive techniques in data visualizations caused participants to misinterpret the information in the deceptive data visualizations even when they were accompanied by a paragraph of explanatory text. Furthermore, certain demographics and comfort levels with chart types were more susceptible to certain types of deceptive techniques. These results highlight the importance of education and practice in the area of data visualizations to ensure deceptive practices are not utilized and to avoid potential misinformation, especially when information can be called into question.
ContributorsO'Brien, Shaun (Author) / Laure, Claire (Thesis advisor) / Brumberger, Eva (Committee member) / D'Angelo, Barbara J. (Committee member) / Arizona State University (Publisher)
Created2017
Description
In this thesis a community-based ride sharing mobile application, Ride Devil, will be introduced and created to provide services for communities such as Arizona State University and its students, faculty, and other affiliates to find safe rides around campus because campus population problem exists. This causes increased transportation costs, decreased parking space availability, and more transportation issues. The Ride Devil application itself is based off on the ride-sharing concept of transportation as introduced, above. Students, faculty, and other university affiliates will drive their own vehicles and use the Ride Devil services in order to coordinate pick-ups with members of its community. Not only is this form of transportation more cost effective than competing transportation models, taxis, but it also promotes safety, community, and educational assistance.
ContributorsVan Hook, Ryan Leo (Author) / Lin, Elva (Thesis director) / Peck, Sidnee (Committee member) / Barrett, The Honors College (Contributor) / Department of Supply Chain Management (Contributor) / W. P. Carey School of Business (Contributor) / Department of Management (Contributor)
Created2014-05
Description
The purpose of this thesis was to develop a tool to provide information and data for design teams to use throughout the mobile application design process. Ideally, this would enable teams to see patterns in iterative design, and ultimately use data-driven analysis to make their own decisions. The initial problem was a lack of available information offered by mobile application design teams—the initial goal being to work closely with design teams to learn their decision-making methodology. However, every team that was reached out to responded with rejection, presenting a new problem: a lack of access to quality information regarding the decision-making process for mobile applications. This problem was addressed by the development of an ethical hacking script that retrieves reviews in bulk from the Google Play Store using Python. The project was a success—by feeding an application’s unique Play Store ID, the script retrieves a user-specified amount of reviews (up to millions) for that mobile application and the 4 “recommended” applications from the Play Store. Ultimately, this thesis proved that protected reviews on the Play Store can be ethically retrieved and used for data-driven decision making and identifying patterns in an application’s iterative design. This script provides an automated tool for teams to “put a finger on the pulse” of their target applications.
ContributorsDyer, Mitchell Patrick (Author) / Lin, Elva (Thesis director) / Giles, Charles (Committee member) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Grubhub's user reviews from the Apple IOS store were analyzed to provide alternate user experience (UX) solutions through answering the following:
1. How is Grubhub's mobile app meeting user expectations?
2. How can Grubhub improve the mobile app experience?
ContributorsDiaz, Samantha (Author) / Harris, LaVerne Abe (Degree committee member) / D'Angelo, Barbara J. (Degree committee member) / Mara, Andrew (Degree committee member)
Created2019-12-13