Matching Items (5)
Filtering by
- Genre: Doctoral Dissertation
- Creators: Arizona State University
Description
This dissertation research analyzes the vernacular cosmopolitan praxis of Muslim women in transnational cyberspaces related to topical and collective action networks, in an effort to detangle cosmopolitanism from its Western biases and to move away from studies of online Muslim populations based on geographical locations or homogenous networks, linking individuals through their religious practices or consumption of religious knowledge. Through highlighting praxes rather than contexts, this dissertation disrupts the East/West binary and challenges stereotypes ascribed to Muslim women. One of the research questions related to the cosmopolitan praxis of Muslim women is the following: in what ways do Muslim women engage with "others" online and contribute to bridging dissimilar people? Findings suggest that the social media use of Muslim women contributes to their subtle resistance against communal norms and, although it can serve as an extension to their voices, some of their voices are more readily mediated than others. I employ a connective content analysis methodology to put various datasets associated with topics and collective actions related to Muslim women into conversation. The methodology not only highlights consistencies in the qualitative themes that were iteratively developed through the analyses of the datasets, but also more tangible connections related to social media users, topics, and content. Consequently, this thesis is as much concerned with recasting Western-oriented conceptualizations of cosmopolitanism as it is with how networks dynamics foster and constrain cosmopolitan praxis because digital networks have the extraordinary capacity to link dissimilar people beyond any other type of medium. One of the research questions related to the methodology is: how do network dynamics facilitate and constrain cosmopolitan praxis? The substantive chapters related to the datasets discuss various forms of cosmopolitan praxis that were identified in the analysis: social media use by Muslim women that expands the connective memory, which could contribute to dispelling stereotypes ascribed to them; activism that addresses universal concerns related to women's rights regardless of context; dialogically devising basic standards of social conduct and gender relations; and expressions of tolerance toward divergent views, including alternative interpretations of Islamic beliefs and practices.
ContributorsRobinson, Rebecca S (Author) / Lim, Merlyna (Thesis advisor) / Ali, Souad T. (Committee member) / Parmentier, Mary Jane C, (Committee member) / Arizona State University (Publisher)
Created2014
Description
This dissertation theorizes Bad Faith Rhetorics, or, rhetorical gestures that work to derail, block, or otherwise stymy knowledge-building efforts. This work explores the ways that interventions against existing social hierarchies (i.e., feminist and antiracist interventions) build knowledge (that is, are epistemologically active), and the ways that bad faith rhetorics derail such interventions. This dissertation demonstrates how bad faith rhetorics function to defend the status quo, with its social stratification by race, gender, class, and other intersectional axes of identity. Bad faith argumentative maneuvers are abundant in online environments. Consequently, this dissertation offers two case studies of the comment sections of two TED Talks: Mellody Hobson’s “Color Blind or Color Brave?” and Juno Mac’s “The Laws that Sex Workers Really Want.” The central analyses deploy online ethnographic field methods and close reading to characterize bad faith rhetorical responses and to identify 1.) trends in such responses, 2.) the net effects on other conversational participants, and 3.) bad faith rhetoric mitigation strategies. This work engages Sartre’s work on Bad Faith, rhetoric scholarship on the knowledge-building affordances of argument, public sphere theory, critical race studies, and feminist scholarship. This dissertation’s theorization and case studies illustrate the pitfalls of specific counterproductive argumentative tactics that block progress toward more equitable ways of being (bad faith rhetorics), and makes several preliminary recommendations for mitigating such moves.
ContributorsFulton-Babicke, Holly Lynn (Author) / Goggin, Maureen (Thesis advisor) / Miller, Keith (Committee member) / Brouwer, Daniel (Committee member) / Arizona State University (Publisher)
Created2019
Description
Public organizations have been interested in tapping into the creativity and passion of the public through the use of open innovation, which emphasizes bottom-up ideation and collaboration. A challenge for organizational adoption of open innovation is that the quick-start, bottom-up, iterative nature of open innovation does not integrate easily into the hierarchical, stability-oriented structure of most organizations. In order to realize the potential of open innovation, organizations must be willing to change the way they operate. This dissertation is a case study of how Arizona State University (ASU), has adapted its organizational structure and created unique programming to incorporate open innovation. ASU has made innovation, inclusion, access, and real world impact organizational priorities in its mission to be the New American University. The primarily focus of the case study is the experiential knowledge of administrative leaders and administrative intermediaries who have managed open innovation programming at the university over the past five years. Using theoretical pattern matching, administrator insights on open innovation adoption are illustrated in terms of design stages, teamwork, and ASU's culture of innovation. It is found that administrators view iterative experimentation with goals of impact as organizational priorities. Institutional support for iterative, experimental programming, along with the assumption that not every effort will be successful, empowers administrators to push to be bolder in their implementation of open innovation. Theoretical pattern matching also enabled a detailed study of administrator alignment regarding one particular open innovation program, the hybrid participatory platform 10,000 Solutions. Creating a successful and meaningful hybrid platform is much more complex than administrators anticipated at the outset. This chapter provides administrator insights in the design, management, and evaluation of participatory platforms. Next, demographic assessment of student participation in open innovation programming is presented. Demographics are found to be reflective of the university population and provide indicators for how to improve existing programming. This dissertation expands understanding of the task facing administrators in an organization seeking to integrate open innovation into their work.
ContributorsKelley, Tanya M (Author) / Johnston, Erik W., 1977- (Thesis advisor) / Schugurensky, Daniel, 1958- (Committee member) / Mossberger, Karen (Committee member) / Longo, Justin (Committee member) / Arizona State University (Publisher)
Created2016
Description
This study tested the preliminary effectiveness of a health belief and text messaging intervention for parents of five- to eight-year-old children to determine whether health beliefs and influenza vaccine receipt differ when compared to a text messaging control group. Children are almost four times more likely to be infected with influenza than adults (Belshe Piedra, & Block, 2009), shed the greatest quantities of influenza virus, and have been recognized as vectors for spread of disease (Neuzil, Mellen, Wright, Mitchel, Jr., & Griffin, 2002b). The influenza immunization rate for school-age children is less than 56% (Centers for Disease Control and Prevention [CDC], 2014). Reasons for the low vaccination rate include parents’ misperceptions of influenza disease and vaccinations (Bhat-Schelbert et al., 2012; Taylor et al., 2002). There are few theory-based interventions for increasing influenza vaccination rates of school-age children; however, promising results have been found when using the constructs of the health belief model (HBM) (Chen et al., 2011; Coe, Gatewood, Moczygemba, Goode, & Beckner, 2012). Mobile technology using Short Message Service (SMS) text messaging may increase vaccination rates to a greater extent than traditional vaccine reminders (Daley et al., 2002; Grajalva, 2006). Prior to starting this study, only one randomized controlled trial testing text messaging to increase children’s influenza vaccination rates was found (Stockwell et al., 2012). In this study, text messaging was effective in promoting behavioral changes leading to a 4% increase in influenza vaccination (27.1% vs. 22.8%, RR = 1.19, p < .001). This study was a randomized controlled trial using a two-group pre- and posttest experimental design. This study found that a theory-based intervention (SayNo2Flu) guided by the HBM and combined with the use of mobile technology (SMS text messaging) did change parents’ influenza vaccination perceptions. It had an overall increase of 38.1% in Influenza vaccination rates in the intervention group (OR: 4.46, 95% CL, 1.705-11.706, p < .001). These results offer some insight into the use of theory-based preventative interventions for parents of young school-age children.
ContributorsWiseman, Patricia (Author) / Reifsnider, Elizabeth G. (Thesis advisor) / Cesarotti, Evelyn (Committee member) / Black, Andy (Committee member) / Kim, Sunny (Committee member) / Arizona State University (Publisher)
Created2015
Description
The rapid advancements of technology have greatly extended the ubiquitous nature of smartphones acting as a gateway to numerous social media applications. This brings an immense convenience to the users of these applications wishing to stay connected to other individuals through sharing their statuses, posting their opinions, experiences, suggestions, etc on online social networks (OSNs). Exploring and analyzing this data has a great potential to enable deep and fine-grained insights into the behavior, emotions, and language of individuals in a society. This proposed dissertation focuses on utilizing these online social footprints to research two main threads – 1) Analysis: to study the behavior of individuals online (content analysis) and 2) Synthesis: to build models that influence the behavior of individuals offline (incomplete action models for decision-making).
A large percentage of posts shared online are in an unrestricted natural language format that is meant for human consumption. One of the demanding problems in this context is to leverage and develop approaches to automatically extract important insights from this incessant massive data pool. Efforts in this direction emphasize mining or extracting the wealth of latent information in the data from multiple OSNs independently. The first thread of this dissertation focuses on analytics to investigate the differentiated content-sharing behavior of individuals. The second thread of this dissertation attempts to build decision-making systems using social media data.
The results of the proposed dissertation emphasize the importance of considering multiple data types while interpreting the content shared on OSNs. They highlight the unique ways in which the data and the extracted patterns from text-based platforms or visual-based platforms complement and contrast in terms of their content. The proposed research demonstrated that, in many ways, the results obtained by focusing on either only text or only visual elements of content shared online could lead to biased insights. On the other hand, it also shows the power of a sequential set of patterns that have some sort of precedence relationships and collaboration between humans and automated planners.
A large percentage of posts shared online are in an unrestricted natural language format that is meant for human consumption. One of the demanding problems in this context is to leverage and develop approaches to automatically extract important insights from this incessant massive data pool. Efforts in this direction emphasize mining or extracting the wealth of latent information in the data from multiple OSNs independently. The first thread of this dissertation focuses on analytics to investigate the differentiated content-sharing behavior of individuals. The second thread of this dissertation attempts to build decision-making systems using social media data.
The results of the proposed dissertation emphasize the importance of considering multiple data types while interpreting the content shared on OSNs. They highlight the unique ways in which the data and the extracted patterns from text-based platforms or visual-based platforms complement and contrast in terms of their content. The proposed research demonstrated that, in many ways, the results obtained by focusing on either only text or only visual elements of content shared online could lead to biased insights. On the other hand, it also shows the power of a sequential set of patterns that have some sort of precedence relationships and collaboration between humans and automated planners.
ContributorsManikonda, Lydia (Author) / Kambhampati, Subbarao (Thesis advisor) / Liu, Huan (Committee member) / Li, Baoxin (Committee member) / De Choudhury, Munmun (Committee member) / Kamar, Ece (Committee member) / Arizona State University (Publisher)
Created2019