Matching Items (4)
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- All Subjects: Social Media
- Creators: Corman, Steven
- Creators: Halavais, Alexander
- Member of: ASU Electronic Theses and Dissertations
- Resource Type: Text
Description
This research start utilizing an efficient sparse inverse covariance matrix (precision matrix) estimation technique to identify a set of highly correlated discriminative perspectives between radical and counter-radical groups. A ranking system has been developed that utilizes ranked perspectives to map Islamic organizations on a set of socio-cultural, political and behavioral scales based on their web site corpus. Simultaneously, a gold standard ranking of these organizations was created through domain experts and compute expert-to-expert agreements and present experimental results comparing the performance of the QUIC based scaling system to another baseline method for organizations. The QUIC based algorithm not only outperforms the baseline methods, but it is also the only system that consistently performs at area expert-level accuracies for all scales. Also, a multi-scale ideological model has been developed and it investigates the correlates of Islamic extremism in Indonesia, Nigeria and UK. This analysis demonstrate that violence does not correlate strongly with broad Muslim theological or sectarian orientations; it shows that religious diversity intolerance is the only consistent and statistically significant ideological correlate of Islamic extremism in these countries, alongside desire for political change in UK and Indonesia, and social change in Nigeria. Next, dynamic issues and communities tracking system based on NMF(Non-negative Matrix Factorization) co-clustering algorithm has been built to better understand the dynamics of virtual communities. The system used between Iran and Saudi Arabia to build and apply a multi-party agent-based model that can demonstrate the role of wedges and spoilers in a complex environment where coalitions are dynamic. Lastly, a visual intelligence platform for tracking the diffusion of online social movements has been developed called LookingGlass to track the geographical footprint, shifting positions and flows of individuals, topics and perspectives between groups. The algorithm utilize large amounts of text collected from a wide variety of organizations’ media outlets to discover their hotly debated topics, and their discriminative perspectives voiced by opposing camps organized into multiple scales. Discriminating perspectives is utilized to classify and map individual Tweeter’s message content to social movements based on the perspectives expressed in their tweets.
ContributorsKim, Nyunsu (Author) / Davulcu, Hasan (Thesis advisor) / Sen, Arunabha (Committee member) / Hsiao, Sharon (Committee member) / Corman, Steven (Committee member) / Arizona State University (Publisher)
Created2018
Description
Long before “fake news” dominated the conversation within and about the media, media literacy advocates have championed the need for media literacy education that provides the tools for people to understand, analyze, and evaluate media messages. That the majority of U.S. adults now consume news on social media underscores the importance for students of all ages to be critical users of media. Furthermore, the affordances of social media to like, comment, and share news items within one’s network increases an individual’s responsibility to ascertain the veracity of news before using a social media megaphone to spread false information. Social media’s shareability can dictate how information spreads, increasing news consumers’ role as a gatekeeper of information and making media literacy education more important than ever.
This research examines the media literacy practices that news consumers use to inform their gatekeeping decisions. Using a constant comparative coding method, the author conducted a qualitative analysis of hundreds of discussion board posts from adult participants in a digital media literacy Massive Open Online Course (MOOC) to identify major themes and examine growth in participants’ sense of responsibility related to sharing news information, their feeling of empowerment to make informed decisions about the media messages they receive, and how the media literacy tools and techniques garnered from the MOOC have affected their daily media interactions. Findings emphasize the personal and contextual nature of media literacy, and that those factors must be addressed to ensure the success of a media literacy education program.
This research examines the media literacy practices that news consumers use to inform their gatekeeping decisions. Using a constant comparative coding method, the author conducted a qualitative analysis of hundreds of discussion board posts from adult participants in a digital media literacy Massive Open Online Course (MOOC) to identify major themes and examine growth in participants’ sense of responsibility related to sharing news information, their feeling of empowerment to make informed decisions about the media messages they receive, and how the media literacy tools and techniques garnered from the MOOC have affected their daily media interactions. Findings emphasize the personal and contextual nature of media literacy, and that those factors must be addressed to ensure the success of a media literacy education program.
ContributorsRoschke, Kristy (Author) / Thornton, Leslie-Jean (Thesis advisor) / Chadha, Monica (Committee member) / Halavais, Alexander (Committee member) / Silcock, Bill (Committee member) / Arizona State University (Publisher)
Created2018
Description
Social media has become a primary means of communication and a prominent source of information about day-to-day happenings in the contemporary world. The rise in the popularity of social media platforms in recent decades has empowered people with an unprecedented level of connectivity. Despite the benefits social media offers, it also comes with disadvantages. A significant downside to staying connected via social media is the susceptibility to falsified information or Fake News. Easy accessibility to social media and lack of truth verification tools favored the miscreants on online platforms to spread false propaganda at scale, ensuing chaos. The spread of misinformation on these platforms ultimately leads to mistrust and social unrest. Consequently, there is a need to counter the spread of misinformation which could otherwise have a detrimental impact on society. A notable example of such a case is the 2019 Covid pandemic misinformation spread, where coordinated misinformation campaigns misled the public on vaccination and health safety. The advancements in Natural Language Processing gave rise to sophisticated language generation models that can generate realistic-looking texts. Although the current Fake News generation process is manual, it is just a matter of time before this process gets automated at scale and generates Neural Fake News using language generation models like the Bidirectional Encoder Representations from Transformers (BERT) and the third generation Generative Pre-trained Transformer (GPT-3). Moreover, given that the current state of fact verification is manual, it calls for an urgent need to develop reliable automated detection tools to counter Neural Fake News generated at scale. Existing tools demonstrate state-of-the-art performance in detecting Neural Fake News but exhibit a black box behavior. Incorporating explainability into the Neural Fake News classification task will build trust and acceptance amongst different communities and decision-makers. Therefore, the current study proposes a new set of interpretable discriminatory features. These features capture statistical and stylistic idiosyncrasies, achieving an accuracy of 82% on Neural Fake News classification. Furthermore, this research investigates essential dependency relations contributing to the classification process. Lastly, the study concludes by providing directions for future research in building explainable tools for Neural Fake News detection.
ContributorsKarumuri, Ravi Teja (Author) / Liu, Huan (Thesis advisor) / Corman, Steven (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2022
Description
Social media has been extensively researched, and its effects on well-being are well established. What is less studied, however, is how social media affects romantic relationships specifically. The few studies that have researched this have found mixed results. Some researchers have found social media to have a positive influence on relationship outcomes, while other have found social media to have a negative influence. In an attempt to reconcile these discrepancies, the current thesis study explored possible mediators between social media use and relationship health outcomes which, to my knowledge, has not been investigated in previous literature. Three moderators were explored: type of social media use (active use versus passive use), relationship-contingent self-esteem, and social comparison orientation. The baseline portion of the study had 547 individuals, recruited from Arizona State University’s SONA system as well as Amazon’s Mechanical Turk, who were in a romantic relationship for at least three months; the follow-up portion of the study had 181 participants. Results suggest that women who passively use social media exhibit a negative association between hours per day of social media use and baseline relationship satisfaction. Men who passively use social media exhibited a negative association between hours per day of social media use and follow-up relationship satisfaction, as well as a negative association with baseline commitment. While relationship-contingent self-esteem did not moderate the association between hours per day of social media use and relationship health, it was positively related to both men and women’s baseline relationship satisfaction and baseline commitment. Social comparison orientation (SCO) produced minimal results; women low on SCO exhibited a negative association between social media use and baseline relationship satisfaction, and higher SCO for men was associated with lower baseline commitment. Finally, exploratory post-hoc mediation models revealed that relationship comparisons mediated the association between hours per day of social media use and baseline relationship, as well as baseline commitment, for both men and women. Previous research supports the findings regarding passive social media use, while the findings regarding relationship-contingent self-esteem and relationship comparisons add new findings to the romantic relationship literature.
ContributorsQuiroz, Selena (Author) / Mickelson, Kristin (Thesis advisor) / Burleson, Mary (Committee member) / Halavais, Alexander (Committee member) / Arizona State University (Publisher)
Created2019