ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
Filtering by
- All Subjects: Social Research
The purpose of this study is to explore how LDS (Mormon) fans of Stephenie Meyer's Twilight saga make meanings from the text in the blogging community known as the Bloggernacle. It investigates how fans recognize, reflect, reinterpret, and resist meanings surrounding multiple Big "D" Discourses (Gee, 1999/2010; 2011) in and around the text. It examines the ways in which LDS fans (Church of Jesus Christ of Latter-day Saints) of the Twilight saga use language in order to signify membership in a particular Discourse. In addition, it seeks to understand how LDS fans use language to perform various identities and position themselves and others within the digital space.
This dissertation study analyzes the threads of five blogs and three discussion forums using the combined methods of critical ethnography (Carspecken, 1996) and Gee's (1999, 2010;2011) discourse analysis. It concludes, that, while multiple Discourses are present within the conversational threads, mainstream Mormon Discourse remains dominant and normalized within the space, which both informs and limits the interpretations available to Mormon fans. In addition, identity performance is negotiated in the blogs, and members form specific sub-communities within the Bloggernacle so as to create a space for those with distinct ways of believing, valuing, knowing, and identifying.
Findings suggest the university's response significantly impacted the retention and enrollment of its American Indian students. Although a majority of the student activists reported feeling isolated or pushed out by the institution, they did not let this deter them from engaging in other social justice oriented efforts and remained dedicated to the pursuit of social justice and/or the protection of American Indian education rights long after they left the in institution. Students exercised agency and demonstrated personal resilience when, upon realizing the university environment was not malleable, responsive, or conducive to their concerns, they left to advocate for justice struggles elsewhere. Unfortunately for some, the university's strong resistance to their efforts caused some to exit the institution before they had completed their degree.
A user vulnerability can be managed in three steps: (1) identifying, (2) measuring and (3) reducing a user vulnerability. Researchers have long been identifying vulnerabilities arising from user's personal data, including user names, demographic attributes, lists of friends, wall posts and associated interactions, multimedia data such as photos, audios and videos, and tagging of friends. Hence, this research first proposes a way to measure and reduce a user vulnerability to protect such personal data. This dissertation also proposes an algorithm to minimize a user's vulnerability while maximizing their social utility values.
To address these vulnerability concerns, social networking sites like Facebook usually let their users to adjust their profile settings so as to make some of their data invisible. However, users sometimes interact with others using unprotected posts (e.g., posts from a ``Facebook page\footnote{The term ''Facebook page`` refers to the page which are commonly dedicated for businesses, brands and organizations to share their stories and connect with people.}''). Such interactions help users to become more social and are publicly accessible to everyone. Thus, visibilities of these interactions are beyond the control of their profile settings. I explore such unprotected interactions so that users' are well aware of these new vulnerabilities and adopt measures to mitigate them further. In particular, {\em are users' personal attributes predictable using only the unprotected interactions}? To answer this question, I address a novel problem of predictability of users' personal attributes with unprotected interactions. The extreme sparsity patterns in users' unprotected interactions pose a serious challenge. Therefore, I approach to mitigating the data sparsity challenge by designing a novel attribute prediction framework using only the unprotected interactions. Experimental results on Facebook dataset demonstrates that the proposed framework can predict users' personal attributes.