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- Genre: Doctoral Dissertation
- Creators: Arizona State University
Description
Teacher attrition and the migration between schools and districts can have a negative impact on quality of education and teacher performance. Novice teachers leave the profession because they are overwhelmed by the workload and responsibilities of the job. In a previous action research cycle, I found that novice teachers' perceptions of isolation and lack of opportunities to share experiences had a negative effect on teacher perceptions of efficacy. This action research project examines the effect of leveraging social media and professional learning communities to provide opportunities for a group of novice teachers to share experiences and seek advice. By addressing the challenges that novice teachers face and providing solutions for common problems, it is the hope of this researcher that highly effective teachers will remain in the classroom. The results of the study indicate that the combined use of Twitter and YouTube in collaboration with professional learning communities will improve teacher perceptions of efficacy. Teachers who participated in the social media based professional learning communities are also more likely to remain in the classroom.
ContributorsBostick, Bradley Alan (Author) / Zambo, Ronald (Thesis advisor) / Heck, Thomas (Committee member) / Isai, Shelley (Committee member) / Arizona State University (Publisher)
Created2013
Description
Social media offers a powerful platform for the independent digital content producer community to develop, disperse, and maintain their brands. In terms of information systems research, the broad majority of the work has not examined hedonic consumption on Social Media Sites (SMS). The focus has mostly been on the organizational perspectives and utilitarian gains from these services. Unlike through traditional commerce channels, including e-commerce retailers, consumption enhancing hedonic utility is experienced differently in the context of a social media site; consequently, the dynamic of the decision-making process shifts when it is made in a social context. Previous research assumed a limited influence of a small, immediate group of peers. But the rules change when the network of peers expands exponentially. The assertion is that, while there are individual differences in the level of susceptibility to influence coming from others, these are not the most important pieces of the analysis--unlike research centered completely on influence. Rather, the context of the consumption can play an important role in the way social influence factors affect consumer behavior on Social Media Sites. Over the course of three studies, this dissertation will examine factors that influence consumer decision-making and the brand personalities created and interpreted in these SMS. Study one examines the role of different types of peer influence on consumer decision-making on Facebook. Study two observes the impact of different types of producer message posts with the different types of influence on decision-making on Twitter. Study three will conclude this work with an exploratory empirical investigation of actual twitter postings of a set of musicians. These studies contribute to the body of IS literature by evaluating the specific behavioral changes related to consumption in the context of digital social media: (a) the power of social influencers in contrast to personal preferences on SMS, (b) the effect on consumers of producer message types and content on SMS at both the profile level and the individual message level.
ContributorsSopha, Matthew (Author) / Santanam, Raghu T (Thesis advisor) / Goul, Kenneth M (Committee member) / Gu, Bin (Committee member) / Arizona State University (Publisher)
Created2013
Description
This qualitative case study of 12, eighteen to twenty-four-year-olds from seven countries provided insight into the learning practices on an art-centered, social media platform. The study addressed two guiding questions; (a) what art related skills, knowledge, and dispositions do community members acquire using a social media platform? (b), What new literacy practices, e.g., the use of new technologies and an ethos of participation, collective intelligence, collaboration, dispersion of abundant resources, and sharing (Knobel & Lankshear, 2007), do members use in acquiring of art-related skills, concepts, knowledge, and dispositions? Data included interviews, online documents, artwork, screen capture of online content, threaded online discussions, and a questionnaire. Drawing on theory and research from both new literacies and art education, the study identified five practices related to learning in the visual arts: (a) practicing as professional artists; (b) engaging in discovery based search strategies for viewing and collecting member produced content; (c) learning by observational strategies; (d) giving constructive criticism and feedback; (e) making learning resources. The study presents suggestions for teachers interested in empowering instruction with new social media technologies.
ContributorsJones, Brian (Author) / Stokrocki, Mary (Thesis advisor) / Young, Bernard (Committee member) / Guzzetti, Barbara (Committee member) / Arizona State University (Publisher)
Created2012
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
Attack of the Fake Geek Girls: Challenging Gendered Harassment and Marginalization in Online Spaces applies feminist, gender, and rhetorical theories and methods, along with critical discourse analysis, to case studies of the popular online social media platforms of Jezebel, Pinterest, and Facebook. This project makes visible the structural inequities that underpin the design and development of internet technologies, as well as commonplace assumptions about who is an online user, who is an active maker of internet technologies, and who is a passive consumer of internet technologies. Applying these critical lenses to these inequities and assumptions enables a re-seeing of commonplace understandings of the relationship between gender performativity and digital cultures and practices. Together, these lenses provide a useful set of tools for methodically resisting the mystique of technologies that are, simultaneously, represented as so highly technical as to be opaque to scrutiny, and as ubiquitous to everyday life as to be beneath critical examination.
Through a close reading of the discourses surrounding these popular social media platforms and a rhetorical analysis of their technological affordances, I documented the transference of gender-biased assumptions about women's roles, interests, and competencies, which have historically been found in face-to-face contexts, to these digital spaces. For example, cultural assumptions about the frivolity of women's interests, endeavors, issues, and labors make their way into digital discourse that situates the online practices of women as those of passive consumers who use the internet only to shop and socialize, rather than to go about the serious, masculine business of making original digital content.
This project expands on existing digital identity and performativity research, while applying a sorely needed feminist critique to online discourses and discursive practices that assume maleness and masculinity as the default positionality. These methods are one approach to addressing the pressing problems of online harassment, the gender gap in the technology sector, and the gender gap in digital literacies that have pedagogical, political, and structural implications for the classroom, workplace, economic markets, and civic sphere.
Through a close reading of the discourses surrounding these popular social media platforms and a rhetorical analysis of their technological affordances, I documented the transference of gender-biased assumptions about women's roles, interests, and competencies, which have historically been found in face-to-face contexts, to these digital spaces. For example, cultural assumptions about the frivolity of women's interests, endeavors, issues, and labors make their way into digital discourse that situates the online practices of women as those of passive consumers who use the internet only to shop and socialize, rather than to go about the serious, masculine business of making original digital content.
This project expands on existing digital identity and performativity research, while applying a sorely needed feminist critique to online discourses and discursive practices that assume maleness and masculinity as the default positionality. These methods are one approach to addressing the pressing problems of online harassment, the gender gap in the technology sector, and the gender gap in digital literacies that have pedagogical, political, and structural implications for the classroom, workplace, economic markets, and civic sphere.
ContributorsTekobbe, Cindy (Author) / Miller, Keith D. (Thesis advisor) / Rose, Shirley K. (Committee member) / Boyd, Patricia (Committee member) / Arizona State University (Publisher)
Created2015
Description
Crises or large-scale emergencies such as earthquakes and hurricanes cause massive damage to lives and property. Crisis response is an essential task to mitigate the impact of a crisis. An effective response to a crisis necessitates information gathering and analysis. Traditionally, this process has been restricted to the information collected by first responders on the ground in the affected region or by official agencies such as local governments involved in the response. However, the ubiquity of mobile devices has empowered people to publish information during a crisis through social media, such as the damage reports from a hurricane. Social media has thus emerged as an important channel of information which can be leveraged to improve crisis response. Twitter is a popular medium which has been employed in recent crises. However, it presents new challenges: the data is noisy and uncurated, and it has high volume and high velocity. In this work, I study four key problems in the use of social media for crisis response: effective monitoring and analysis of high volume crisis tweets, detecting crisis events automatically in streaming data, identifying users who can be followed to effectively monitor crisis, and finally understanding user behavior during crisis to detect tweets inside crisis regions. To address these problems I propose two systems which assist disaster responders or analysts to collaboratively collect tweets related to crisis and analyze it using visual analytics to identify interesting regions, topics, and users involved in disaster response. I present a novel approach to detecting crisis events automatically in noisy, high volume Twitter streams. I also investigate and introduce novel methods to tackle information overload through the identification of information leaders in information diffusion who can be followed for efficient crisis monitoring and identification of messages originating from crisis regions using user behavior analysis.
ContributorsKumar, Shamanth (Author) / Liu, Huan (Thesis advisor) / Davulcu, Hasan (Committee member) / Maciejewski, Ross (Committee member) / Agarwal, Nitin (Committee member) / Arizona State University (Publisher)
Created2015
Description
Writing instruction poses both cognitive and affective challenges, particularly for adolescents. American teens not only fall short of national writing standards, but also tend to lack motivation for school writing, claiming it is too challenging and that they have nothing interesting to write about. Yet, teens enthusiastically immerse themselves in informal writing via text messaging, email, and social media, regularly sharing their thoughts and experiences with a real audience. While these activities are, in fact, writing, research indicates that teens instead view them as simply "communication" or "being social." Accordingly, the aim of this work was to infuse formal classroom writing with naturally engaging elements of informal social media writing to positively impact writing quality and the motivation to write, resulting in the development and implementation of Sparkfolio, an online prewriting tool that: a) addresses affective challenges by allowing students to choose personally relevant topics using their own social media data; and b) provides cognitive support with a planner that helps develop and organize ideas in preparation for writing a first draft. This tool was evaluated in a study involving 46 eleventh-grade English students writing three personal narratives each, and including three experimental conditions: a) using self-authored social media post data while planning with Sparkfolio; b) using only data from posts authored by one's friends while planning with Sparkfolio; and c) a control group that did not use Sparkfolio. The dependent variables were the change in writing motivation and the change in writing quality that occurred before and after the intervention. A scaled pre/posttest measured writing motivation, and the first and third narratives were used as writing quality pre/posttests. A usability scale, logged Sparkfolio data, and qualitative measures were also analyzed. Results indicated that participants who used Sparkfolio had statistically significantly higher gains in writing quality than the control group, validating Sparkfolio as effective. Additionally, while nonsignificant, results suggested that planning with self-authored data provided more writing quality and motivational benefits than data authored by others. This work provides initial empirical evidence that leveraging students' own social media data (securely) holds potential in fostering meaningful personalized learning.
ContributorsSadauskas, John (Author) / Atkinson, Robert K (Thesis advisor) / Savenye, Wilhelmina (Committee member) / Liu, Huan (Committee member) / Arizona State University (Publisher)
Created2014
Description
The overall purpose of this study was to explore the dynamics of teaching and learning in the context of an informal, online discussion forum. This investigation utilized the Community of Inquiry (CoI) elements of Teaching Presence and Social Presence along with the construct of Learning Presence to examine Adobe® Forums, Photoshop® for Beginners Forum (PfBF) an internet discussion forum designed to provide support for beginning users of Adobe Photoshop. The researcher collected four days of discussion post data comprising 62 discussion threads for a total of 202 discussion posts. During this initial pilot analysis, the discussion threads were divided into posts created by members who were deemed to be acting as teachers and posts written by members acting as learners. Three analyses were conducted. First, a pilot analysis was conducted where the researcher divided the data in half and coded 31 discussion threads and a total of 142 discussion posts with the Teaching Presence, Social Presence and Learning Presence coding schemes. Second, a reliability analysis was conducted to determine the interrater reliability of the coding schemes. For this analysis two additional coders were recruited, trained and coded a small subsample of data (4 discussion threads for a total of 29 discussion posts) using the same three coding schemes. Third, a final analysis was conducted where the researcher coded and analyzed 134 discussion posts created by 24 teachers using the Teaching Presence coding scheme. At the conclusion of the final analysis, it was determined that eighteen percent (18%) of the data could not be coded using the Teaching Presence coding scheme. However, this data were observed to contain behavioral indicators of Social Presence. Consequently, the Social Presence coding scheme was used to code and analyze the remaining data. The results of this study revealed that forum members who interact on PfBF do indeed exhibit Teaching Presence behaviors. Direct Instruction was the largest category of Teaching Presence behaviors exhibited, over and above Facilitating Discussion and Design and Organization. It was also observed that forum members serving in the role of teachers exhibit behaviors of Social Presence alongside Teaching Presence behaviors.
ContributorsWilliams, Indi Marie (Author) / Gee, Elizabeth (Thesis advisor) / Olaniran, Bolanle (Committee member) / Nelson, Brian (Committee member) / Arizona State University (Publisher)
Created2014
Description
With the rise of social media, hundreds of millions of people spend countless hours all over the globe on social media to connect, interact, share, and create user-generated data. This rich environment provides tremendous opportunities for many different players to easily and effectively reach out to people, interact with them, influence them, or get their opinions. There are two pieces of information that attract most attention on social media sites, including user preferences and interactions. Businesses and organizations use this information to better understand and therefore provide customized services to social media users. This data can be used for different purposes such as, targeted advertisement, product recommendation, or even opinion mining. Social media sites use this information to better serve their users.
Despite the importance of personal information, in many cases people do not reveal this information to the public. Predicting the hidden or missing information is a common response to this challenge. In this thesis, we address the problem of predicting user attributes and future or missing links using an egocentric approach. The current research proposes novel concepts and approaches to better understand social media users in twofold including, a) their attributes, preferences, and interests, and b) their future or missing connections and interactions. More specifically, the contributions of this dissertation are (1) proposing a framework to study social media users through their attributes and link information, (2) proposing a scalable algorithm to predict user preferences; and (3) proposing a novel approach to predict attributes and links with limited information. The proposed algorithms use an egocentric approach to improve the state of the art algorithms in two directions. First by improving the prediction accuracy, and second, by increasing the scalability of the algorithms.
Despite the importance of personal information, in many cases people do not reveal this information to the public. Predicting the hidden or missing information is a common response to this challenge. In this thesis, we address the problem of predicting user attributes and future or missing links using an egocentric approach. The current research proposes novel concepts and approaches to better understand social media users in twofold including, a) their attributes, preferences, and interests, and b) their future or missing connections and interactions. More specifically, the contributions of this dissertation are (1) proposing a framework to study social media users through their attributes and link information, (2) proposing a scalable algorithm to predict user preferences; and (3) proposing a novel approach to predict attributes and links with limited information. The proposed algorithms use an egocentric approach to improve the state of the art algorithms in two directions. First by improving the prediction accuracy, and second, by increasing the scalability of the algorithms.
ContributorsAbbasi, Mohammad Ali, 1975- (Author) / Liu, Huan (Thesis advisor) / Davulcu, Hasan (Committee member) / Ye, Jieping (Committee member) / Agarwal, Nitin (Committee member) / Arizona State University (Publisher)
Created2014
Description
Social media platforms such as Twitter, Facebook, and blogs have emerged as valuable
- in fact, the de facto - virtual town halls for people to discover, report, share and
communicate with others about various types of events. These events range from
widely-known events such as the U.S Presidential debate to smaller scale, local events
such as a local Halloween block party. During these events, we often witness a large
amount of commentary contributed by crowds on social media. This burst of social
media responses surges with the "second-screen" behavior and greatly enriches the
user experience when interacting with the event and people's awareness of an event.
Monitoring and analyzing this rich and continuous flow of user-generated content can
yield unprecedentedly valuable information about the event, since these responses
usually offer far more rich and powerful views about the event that mainstream news
simply could not achieve. Despite these benefits, social media also tends to be noisy,
chaotic, and overwhelming, posing challenges to users in seeking and distilling high
quality content from that noise.
In this dissertation, I explore ways to leverage social media as a source of information and analyze events based on their social media responses collectively. I develop, implement and evaluate EventRadar, an event analysis toolbox which is able to identify, enrich, and characterize events using the massive amounts of social media responses. EventRadar contains three automated, scalable tools to handle three core event analysis tasks: Event Characterization, Event Recognition, and Event Enrichment. More specifically, I develop ET-LDA, a Bayesian model and SocSent, a matrix factorization framework for handling the Event Characterization task, i.e., modeling characterizing an event in terms of its topics and its audience's response behavior (via ET-LDA), and the sentiments regarding its topics (via SocSent). I also develop DeMa, an unsupervised event detection algorithm for handling the Event Recognition task, i.e., detecting trending events from a stream of noisy social media posts. Last, I develop CrowdX, a spatial crowdsourcing system for handling the Event Enrichment task, i.e., gathering additional first hand information (e.g., photos) from the field to enrich the given event's context.
Enabled by EventRadar, it is more feasible to uncover patterns that have not been
explored previously and re-validating existing social theories with new evidence. As a
result, I am able to gain deep insights into how people respond to the event that they
are engaged in. The results reveal several key insights into people's various responding
behavior over the event's timeline such the topical context of people's tweets does not
always correlate with the timeline of the event. In addition, I also explore the factors
that affect a person's engagement with real-world events on Twitter and find that
people engage in an event because they are interested in the topics pertaining to
that event; and while engaging, their engagement is largely affected by their friends'
behavior.
- in fact, the de facto - virtual town halls for people to discover, report, share and
communicate with others about various types of events. These events range from
widely-known events such as the U.S Presidential debate to smaller scale, local events
such as a local Halloween block party. During these events, we often witness a large
amount of commentary contributed by crowds on social media. This burst of social
media responses surges with the "second-screen" behavior and greatly enriches the
user experience when interacting with the event and people's awareness of an event.
Monitoring and analyzing this rich and continuous flow of user-generated content can
yield unprecedentedly valuable information about the event, since these responses
usually offer far more rich and powerful views about the event that mainstream news
simply could not achieve. Despite these benefits, social media also tends to be noisy,
chaotic, and overwhelming, posing challenges to users in seeking and distilling high
quality content from that noise.
In this dissertation, I explore ways to leverage social media as a source of information and analyze events based on their social media responses collectively. I develop, implement and evaluate EventRadar, an event analysis toolbox which is able to identify, enrich, and characterize events using the massive amounts of social media responses. EventRadar contains three automated, scalable tools to handle three core event analysis tasks: Event Characterization, Event Recognition, and Event Enrichment. More specifically, I develop ET-LDA, a Bayesian model and SocSent, a matrix factorization framework for handling the Event Characterization task, i.e., modeling characterizing an event in terms of its topics and its audience's response behavior (via ET-LDA), and the sentiments regarding its topics (via SocSent). I also develop DeMa, an unsupervised event detection algorithm for handling the Event Recognition task, i.e., detecting trending events from a stream of noisy social media posts. Last, I develop CrowdX, a spatial crowdsourcing system for handling the Event Enrichment task, i.e., gathering additional first hand information (e.g., photos) from the field to enrich the given event's context.
Enabled by EventRadar, it is more feasible to uncover patterns that have not been
explored previously and re-validating existing social theories with new evidence. As a
result, I am able to gain deep insights into how people respond to the event that they
are engaged in. The results reveal several key insights into people's various responding
behavior over the event's timeline such the topical context of people's tweets does not
always correlate with the timeline of the event. In addition, I also explore the factors
that affect a person's engagement with real-world events on Twitter and find that
people engage in an event because they are interested in the topics pertaining to
that event; and while engaging, their engagement is largely affected by their friends'
behavior.
ContributorsHu, Yuheng (Author) / Kambhampati, Subbarao (Thesis advisor) / Horvitz, Eric (Committee member) / Krumm, John (Committee member) / Liu, Huan (Committee member) / Sundaram, Hari (Committee member) / Arizona State University (Publisher)
Created2014