Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
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- Creators: Li, Baoxin
Description
Social Computing is an area of computer science concerned with dynamics of communities and cultures, created through computer-mediated social interaction. Various social media platforms, such as social network services and microblogging, enable users to come together and create social movements expressing their opinions on diverse sets of issues, events, complaints, grievances, and goals. Methods for monitoring and summarizing these types of sociopolitical trends, its leaders and followers, messages, and dynamics are needed. In this dissertation, a framework comprising of community and content-based computational methods is presented to provide insights for multilingual and noisy political social media content. First, a model is developed to predict the emergence of viral hashtag breakouts, using network features. Next, another model is developed to detect and compare individual and organizational accounts, by using a set of domain and language-independent features. The third model exposes contentious issues, driving reactionary dynamics between opposing camps. The fourth model develops community detection and visualization methods to reveal underlying dynamics and key messages that drive dynamics. The final model presents a use case methodology for detecting and monitoring foreign influence, wherein a state actor and news media under its control attempt to shift public opinion by framing information to support multiple adversarial narratives that facilitate their goals. In each case, a discussion of novel aspects and contributions of the models is presented, as well as quantitative and qualitative evaluations. An analysis of multiple conflict situations will be conducted, covering areas in the UK, Bangladesh, Libya and the Ukraine where adversarial framing lead to polarization, declines in social cohesion, social unrest, and even civil wars (e.g., Libya and the Ukraine).
ContributorsAlzahrani, Sultan (Author) / Davulcu, Hasan (Thesis advisor) / Corman, Steve R. (Committee member) / Li, Baoxin (Committee member) / Hsiao, Ihan (Committee member) / Arizona State University (Publisher)
Created2018
Description
With the rise of Online Social Networks (OSN) in the last decade, social network analysis has become a crucial research topic. The OSN graphs have unique properties that distinguish them from other types of graphs. In this thesis, five month Tweet corpus collected from Bangladesh - between June 2016 and October 2016 is analyzed, in order to detect accounts that belong to groups. These groups consist of official and non-official twitter handles of political organizations and NGOs in Bangladesh. A set of network, temporal, spatial and behavioral features are proposed to discriminate between accounts belonging to individual twitter users, news, groups and organization leaders. Finally, the experimental results are presented and a subset of relevant features is identified that lead to a generalizable model. Detection of tiny number of groups from large network is achieved with 0.8 precision, 0.75 recall and 0.77 F1 score. The domain independent network and behavioral features and models developed here are suitable for solving twitter account classification problem in any context.
ContributorsGore, Chinmay Chandrashekhar (Author) / Davulcu, Hasan (Thesis advisor) / Hsiao, Ihan (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2017
Description
Bangladesh is a secular democracy with almost 90% of its population constituting of Muslims and the rest 10% constituting of the minority groups that includes Hindus, Christians, Buddhists, Ahmadi Muslims, Shia, Sufi, LGBT groups and Atheists. In recent years, Bangladesh has experienced an increase in attacks by religious extremist groups, such as IS and AQIS affiliates, hate-groups and politically motivated violence. Attacks have also become indiscriminate, with assailants targeting a wide variety of individuals, including religious minorities and foreigners. According to the telecoms regulator, the number of internet users in Bangladesh now stands at over 66.8 million reaching 41% penetration. Of them, 63 million access the internet through mobile phones. Facebook, with the usage of about 97.2%, is the most used social network in Bangladesh.
In this research, local academics with cultural expertise collaborated to locate and download content from 292 Facebook groups organized under three (3) major umbrella types: Religious Terrorist Violence, Political Intolerance and Issue, and Target-based Intolerance between June2016 - December 2016 period. Dates of real extremist attacks were aligned with corresponding Facebook message streams, identified posts and comments related to the targets and perpetrators of the attacks, and proceeded to use the context of the attacks, their effects, the nature and structure of underlying extremist and counter-violent extremist networks, to study the narratives and trends over time.
In this research, local academics with cultural expertise collaborated to locate and download content from 292 Facebook groups organized under three (3) major umbrella types: Religious Terrorist Violence, Political Intolerance and Issue, and Target-based Intolerance between June2016 - December 2016 period. Dates of real extremist attacks were aligned with corresponding Facebook message streams, identified posts and comments related to the targets and perpetrators of the attacks, and proceeded to use the context of the attacks, their effects, the nature and structure of underlying extremist and counter-violent extremist networks, to study the narratives and trends over time.
ContributorsChhabra, Pankaj (Author) / Davulcu, Hasan (Thesis advisor) / Li, Baoxin (Committee member) / Hsiao, Ihan (Committee member) / Arizona State University (Publisher)
Created2017