عنوان

Perspective Scaling and Trait Detection on Social Media Data

Number

TL49906

.Language of Text, Soundtrack etc

انگلیسی

Title Proper

Perspective Scaling and Trait Detection on Social Media Data

General Material Designation

[Thesis]

First Statement of Responsibility

Nyunsu Kim

Subsequent Statement of Responsibility

Davulcu, Hasan

Name of Publisher, Distributor, etc.

Arizona State University

Date of Publication, Distribution, etc.

2018

Specific Material Designation and Extent of Item

94

Text of Note

Committee members: Corman, Steven; Hsiao, Sharon; Sen, Arunabha

Text of Note

Place of publication: United States, Ann Arbor; ISBN=978-0-355-95187-5

Dissertation or thesis details and type of degree

Ph.D.

Discipline of degree

Computer Science

Body granting the degree

Arizona State University

Text preceding or following the note

2018

Text of Note

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 Looking-Glass 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.

Web Studies; Computer science

Subject Term

Applied sciences;Communication and the arts;Clustering;Machine learning;Scaling;Social media;Text mining;Visualization

Habeeb, Noah Elias

Davulcu, Hasan

Subdivision

Computer Science

Arizona State University

Call Number

2046781538; 10810888

Electronic name

p

[Thesis]

276903

a

Y