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Social Network Analysis Approach and...
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White, Joshua S.
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Social Network Analysis Approach and Applications.
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Social Network Analysis Approach and Applications./
Author:
White, Joshua S.
Description:
278 p.
Notes:
Source: Dissertation Abstracts International, Volume: 75-08(E), Section: B.
Contained By:
Dissertation Abstracts International75-08B(E).
Subject:
Computer Science. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3618581
ISBN:
9781303869808
Social Network Analysis Approach and Applications.
White, Joshua S.
Social Network Analysis Approach and Applications.
- 278 p.
Source: Dissertation Abstracts International, Volume: 75-08(E), Section: B.
Thesis (Ph.D.)--Clarkson University, 2014.
Social network analysis is the study of human inter-connectivity; social media sites are those tools which have been created, to enable easier and more prolific communication within these networks. The field of social media network analysis has emerged over the past few years as a viable means of understanding the sentiment of individuals and groups, as they pertain to particular events.
ISBN: 9781303869808Subjects--Topical Terms:
626642
Computer Science.
Social Network Analysis Approach and Applications.
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Source: Dissertation Abstracts International, Volume: 75-08(E), Section: B.
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Adviser: Jeanna N. Matthews.
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Thesis (Ph.D.)--Clarkson University, 2014.
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Social network analysis is the study of human inter-connectivity; social media sites are those tools which have been created, to enable easier and more prolific communication within these networks. The field of social media network analysis has emerged over the past few years as a viable means of understanding the sentiment of individuals and groups, as they pertain to particular events.
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Social media networks make up a large percentage of the content available on the Internet. Most of the time users spend online today, is spent interacting with them. All of the seemingly small pieces of information, added by billions of people, results in an enormous and rapidly changing data-set. Searching, correlating and understanding the billions of individual posts is a significant technical problem; even the data from a single site, such as twitter, can be difficult to manage.
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In this dissertation we describe the overall architecture, including the capture, storage, search, and graph components that we have designed for social network analysis. We present various use cases for the data collected including: the detection of botnet command and control channels, detection of phishing websites, analysis of actor roles, preliminary results in the analysis of trend propagation, and the detection of infection vectors. We describe our experiences with managing a 100+ terabyte data-set. We discuss the complications of large data-set management, our experiences dealing with the evolution of the Twitter REST API, and present strategies for maximizing the amount of data collected.
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Looking forward, we describe some of the new trends in data analysis and knowledge management. We argue our position on one such trend, the use of semantic or linked data, and its affects on individuals privacy.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3618581
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