عنوان

Focal structures analysis in complex and social networks

Number

TL48154

.Language of Text, Soundtrack etc

انگلیسی

Title Proper

Focal structures analysis in complex and social networks

General Material Designation

[Thesis]

First Statement of Responsibility

Fatih Sen

Subsequent Statement of Responsibility

Wigand, Rolf T.

Name of Publisher, Distributor, etc.

University of Arkansas at Little Rock

Date of Publication, Distribution, etc.

2014

Specific Material Designation and Extent of Item

113

Text of Note

Committee members: Agarwal, Nitin; Bush, Keith; Long, Christopher; Xu, Xiaowei

Text of Note

Place of publication: United States, Ann Arbor; ISBN=978-1-321-62158-7

Dissertation or thesis details and type of degree

Ph.D.

Discipline of degree

Computer Science

Body granting the degree

University of Arkansas at Little Rock

Text preceding or following the note

2014

Text of Note

Identifying influential individuals is a well-known approach in extracting actionable knowledge in a network. Previous researches suggest measures to identify influential individuals, e.g., they focus on the question 'which individuals are best connected to others or have the most influence?'. Such individuals, however, might not represent the context (relationships, interactions, etc.) entirely in a social network. For example, it is nearly an impossible task for a single individual to organize a mass protest of the scale of the 2011 Arab Spring and the 2012 Occupy Wall Street. Similarly, other events such as mobilizing the 2013 Taksim square-Gezi Park protesters, coordinating crisis response for natural disasters (e.g., the 2010 Haiti earthquake), or even organizing flash mobs would require a key set of individuals rather than a single or the most influential individual in a social network. An alternate line of research dealing with community or cluster identification approaches extract subnetworks of individuals. However, these structures may not represent the key sets of individuals that could coordinate the social processes mentioned above. Therefore, we develop the Focal Structures Analysis (FSA) methodology to extract such key sets of individuals, called focal structures, in a social network or complex network in general. The FSA methodology looks at either recursive fractioning or network measures to detect focal structures. This research goes beyond the traditional unit of analysis, which is an individual or a set of influential individuals, and places focal structures between the individuals and communities/clusters as the unit of analysis. The current level of developed analysis would benefit the people with far-reaching implications in the industry areas such as recommendation systems, information diffusion, marketing, advertising, cyber-security and search engine indexing, among others. The methodological contributions of this research can help in analyzing and understanding real-world phenomena and advance foundational sociological concepts. To the best of our knowledge, this type of work is the first effort in identifying influential sets of individuals and would open up new directions to researchers who can work further on developing new methods in social network analysis or in complex systems.

Web Studies; Computer science

Subject Term

Communication and the arts;Applied sciences;Complex networks;Focal structures;Social networks

Potorti, Mary E.

Wigand, Rolf T.

Subdivision

Computer Science

University of Arkansas at Little Rock

Call Number

1666453062; 3685750

Electronic name

p

[Thesis]

276903

a

Y