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Description
This paper presents the design and evaluation of a haptic interface for augmenting human-human interpersonal interactions by delivering facial expressions of an interaction partner to an individual who is blind using a visual-to-tactile mapping of facial action units and emotions. Pancake shaftless vibration motors are mounted on the back of a chair to provide vibrotactile stimulation in the context of a dyadic (one-on-one) interaction across a table. This work explores the design of spatiotemporal vibration patterns that can be used to convey the basic building blocks of facial movements according to the Facial Action Unit Coding System. A behavioral study was conducted to explore the factors that influence the naturalness of conveying affect using vibrotactile cues.
ContributorsBala, Shantanu (Author) / Panchanathan, Sethuraman (Thesis director) / McDaniel, Troy (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / Department of Psychology (Contributor)
Created2014-05
Description
CourseKarma is a web application that engages students in their own learning through peer-driven social networking. The influence of technology on students is advancing faster than the school system, and a major gap still lingers between traditional learning techniques and the fast-paced, online culture of today's generation. CourseKarma enriches the educational experience of today's student by creating a space for collaborative inquiry as well as illuminating the opportunities of self and group learning through online collaboration. The features of CourseKarma foster this student-driven environment. The main focus is on a news-feed and Question and Answer component that provides a space for students to share instant updates as well ask and answer questions of the community. The community can be as broad as the entire ASU student body, as specific as students in BIO155, or even more targeted via specific subjects and or skills. CourseKarma also provides reputation points, which are the sum of all of their votes received, identifying the individual's level and or ranking in each subject or class. This not only gamifies the usual day-to-day learning environment, but it also provides an in-depth analysis of the individual's skills, accomplishments, and knowledge. The community is also able to input and utilize course and professor descriptions/feedback. This will be in a review format providing the students an opportunity to share and give feedback on their experience as well as providing incoming students the opportunity to be prepared for their future classes. All of the student's contributions and collaborative activity within CourseKarma is displayed on their personal profile creating a timeline of their academic achievements. The application was created using modern web programming technologies such as AngualrJS, Javascript, jQuery, Bootstrap, HTML5, CSS3 for the styling and front-end development, Mustache.js for client side templating, and Firebase AngularFire as the back-end and NoSQL database. Other technologies such as Pivitol Tracker was used for project management and user story generation, as well as, Github for version control management and repository creation. Object-oreinted programming concepts were heavily present in the creation of the various data structures, as well as, a voting algorithm was used to manage voting of specific posts. Down the road, CourseKarma could even be a necessary add-on within LinkedIn or Facebook that provides a quick yet extremely in-depth look at an individuals' education, skills, and potential to learn \u2014 based all on their actual contribution to their academic community rather than just a text they wrote up.
ContributorsCho, Sungjae (Author) / Mayron, Liam (Thesis director) / Lobock, Alan (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / School of Arts, Media and Engineering (Contributor)
Created2015-05
Description
Although previous research has explored the relationship between social media use and well-being, many studies are contradictory of each other and conclude varying findings relating to social media use and outspokenness. This study explores the relationship between active and passive social media use, perceived social media expertise, and outspokenness using the potentially mediating variable of perceived social acceptance. 162 participants, recruited through Amazon Mechanical Turk (MTurk) and ASU’s SONA systems, completed a survey relating to their own use of social media, perceived social acceptance, and outspokenness. Contradictory to my first hypotheses, no significant correlations were found between social media use and social media expertise. However, correlation analyses revealed that active social media use is related to an increased amount of perceived social media expertise (r = 0.23, p < .004). Perceived social media expertise was significantly positively correlated with outspokenness (r = 0.19, p < 0.015); however, it was not correlated with perceived social acceptance. When examining these relationships separately by gender, a strong association was found for males between active social media use and outspokenness, whereas passive social media use and outspokenness were negatively correlated for females. The results of this study add to previous research in the field of social media and outspokenness and lend new ideas for future research on these topics, such as exploring the gender differences that are associated with these variables. Further research in the area is needed for a more complete understanding of how one’s social media use affects his/her outspokenness and how gender modifies these effects.
ContributorsRubino, Kelli Erika (Co-author) / Rubino, Kelli (Co-author) / Mickelson, Kristin (Thesis director) / Halavais, Alexander (Committee member) / Department of Psychology (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Since the advent of social media, researchers have studied how platforms like Facebook and Instagram can influence our relationships, and more specifically, how social networking sites can impact what happens when these relationships dissolve. Less is known about the newer platform Snapchat, which provides ephemeral updates as they occur to one's friend list, as well as self-destructing direct messages between individuals. The present study utilized survey responses from 84 college-aged individuals and eight semi-structured, in-depth interviews to study the relationship between using Snapchat to engage with or monitor one's ex-partner, the level of distress that results from these behaviors, and an individual's overall breakup distress level. A significant positive correlation was found between each of these variables, indicating that remaining connected with one's ex-partner on Snapchat may contribute to one's level of distress, or alternatively, that more distressed individuals are turning to Snapchat to monitor their ex-partner. Pairing this quantitative data with in-depth interviews allowed for more robust and generalizable findings. Qualitative details supported the statistical analysis to indicate that one's overall breakup distress level may be leading individuals to use Snapchat to monitor their ex-partner or exaggerate their own speed of recovery. Future research should analyze these same variables in a larger, more representative sample by following couples as their breakups occur in real-time to capture more comprehensive participant experiences.
ContributorsAter, Brittany Alexis (Author) / Parker, John (Thesis director) / Bodford, Jessica (Committee member) / Sanford School of Social and Family Dynamics (Contributor) / Department of Marketing (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
In 2012, Chick-fil-A president Dan Cathy's "came out" about his anti-same sex marriage views, launching an enormous negative backlash across social media networks. To counteract this, former governor Mike Huckabee called on his Facebook fans to support the company on "Chick-fil-A Appreciation Day," both on Facebook and in person. The project examines both the backlash and Appreciation Day on social media networks. Posts on the Appreciation Day Facebook event page and similar posts on Twitter were first broken down in the framework of supportive and oppositional posts and then analyzed in further contexts. Comments on official Chick-fil-A Facebook statuses were then examined in a similar fashion. The research concludes that a strong support system both online and offline were necessary for Chick-fil-A to recover from its backlash. The controversy that ensued is ultimately a case study in the growing influence of Facebook as a tool for small-scale activism.
ContributorsKuiland, Zachary Rico (Author) / Cheong, Pauline (Thesis director) / Szeli, Eva (Committee member) / Lim, Merlyna (Committee member) / Barrett, The Honors College (Contributor) / School of Criminology and Criminal Justice (Contributor) / Department of Psychology (Contributor)
Created2013-05
Description
Despite the advancement of online tools for activities related to the core experience of taking classes on a college campus, there has been a relatively small amount of research into implementing online tools for ancillary academic resources (e.g. tutoring centers, review sessions, etc.). Previous work and a study conducted for this paper indicates that there is value in creating these online tools but that there is value in maintaining an in-person component to these services. Based on this, a system which provides personalized, easily-accessible, simple access to these services is proposed. Designs for user-centered online-tools that provides access to and interaction with tutoring centers and review sessions are described and prototypes are developed to demonstrate the application of design principles for online tools for academic services.
ContributorsBerk, Nicholas Robert (Author) / Balasooriya, Janaka (Thesis director) / Eaton, John (Committee member) / Walker, Erin (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-12
Description
Web-application development constantly changes \u2014 new programming languages, testing tools and programming methodologies are often proposed. The focus of this project is on the tool Selenium and the fairly new technique known as High Volume Automated Testing (HVAT). Both of these techniques were used to test the Just-in-Time Teaching and Learning Classroom Management System software. Selenium was used with a black-box testing technique and HVAT was employed in a white-box testing technique. Two of the major functionalities of this software were examined, which include the login and the professor functionality. The results of the black-box testing technique showed parts of the login component contain bugs, but the professor component is clean. HVAT white-box testing revealed error free implementation on the code level. We present an analysis on a new technique for HVAT testing with Selenium.
ContributorsEjaz, Samira (Author) / Balasooriya, Janaka (Thesis director) / Nakamura, Mutsumi (Committee member) / Wilkerson, Kelly (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-05
Description
Social media has quickly become a dominant tool for businesses across all sectors due to its two-way communication capabilities. Previous research has suggested that companies, particularly the hospitality and travel industry, should be engaging in authentic dialogue with its audience members, be using vibrant imagery and be monitoring and promoting user-generated content and electronic-word-of-mouth. These elements were observed for six luxury hotels and resorts in the Southwestern United States over the course of a month on Facebook, Twitter and TripAdvisor. In addition, three two-part electronic-questionnaires were administered to three of the six luxury hotels and resorts to determine industry perspectives on these subjects and to serve as a comparison of social media tactics in this sector. There were social media differences and similarities based on the location and size of the hotel. Facebook was comprised of 42 percent advertising and used large amounts of imagery to promote the properties. There was very little user-generated content and word-of-mouth. Twitter was comprised of 31 percent dialogue and 22 percent user-generated content. Five of the six properties responded to reviews on TripAdvisor. Three crisis responses via social media were also observed. Later research may choose to include more analytic-based research and examine other social media platforms.
ContributorsWininger, Emily Renee (Author) / Wu, Xu (Thesis director) / Ostrom, Amy (Committee member) / Barrett, The Honors College (Contributor) / Department of Psychology (Contributor) / Walter Cronkite School of Journalism and Mass Communication (Contributor) / School of Social Transformation (Contributor)
Created2014-05
Description
Charleston, South Carolina currently faces serious annual flooding issues due to tides and rainfall. These issues are expected to get significantly worse within the next few decades reaching a projected 180 days a year of flooding by 2045 (Carter et al., 2018). Several permanent solutions are in progress by the City of Charleston. However, these solutions are years away at minimum and faced with development issues. This thesis attempts to treat some of the symptoms of flooding, such as navigation, by creating an iPhone application which predicts flooding and helps people navigate around it safely. Specifically, this thesis will take into account rainfall and tide levels to display to users actively flooded areas of downtown Charleston and provide routing to a destination from a user’s location around these flooded areas whenever possible.
ContributorsSalisbury, Mason (Author) / Balasooriya, Janaka (Thesis director) / Faucon, Christophe (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
The prevalence of bots, or automated accounts, on social media is a well-known problem. Some of the ways bots harm social media users include, but are not limited to, spreading misinformation, influencing topic discussions, and dispersing harmful links. Bots have affected the field of disaster relief on social media as well. These bots cause problems such as preventing rescuers from determining credible calls for help, spreading fake news and other malicious content, and generating large amounts of content which burdens rescuers attempting to provide aid in the aftermath of disasters. To address these problems, this research seeks to detect bots participating in disaster event related discussions and increase the recall, or number of bots removed from the network, of Twitter bot detection methods. The removal of these bots will also prevent human users from accidentally interacting with these bot accounts and being manipulated by them. To accomplish this goal, an existing bot detection classification algorithm known as BoostOR was employed. BoostOR is an ensemble learning algorithm originally modeled to increase bot detection recall in a dataset and it has the possibility to solve the social media bot dilemma where there may be several different types of bots in the data. BoostOR was first introduced as an adjustment to existing ensemble classifiers to increase recall. However, after testing the BoostOR algorithm on unobserved datasets, results showed that BoostOR does not perform as expected. This study attempts to improve the BoostOR algorithm by comparing it with a baseline classification algorithm, AdaBoost, and then discussing the intentional differences between the two. Additionally, this study presents the main factors which contribute to the shortcomings of the BoostOR algorithm and proposes a solution to improve it. These recommendations should ensure that the BoostOR algorithm can be applied to new and unobserved datasets in the future.
ContributorsDavis, Matthew William (Author) / Liu, Huan (Thesis director) / Nazer, Tahora H. (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12