Cooperative, dynamic Twitter parsing and visualization for dark network analysis

Dudas, Patrick M.

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https://hdl.handle.net/2142/39982 Copy

Description

Title

Cooperative, dynamic Twitter parsing and visualization for dark network analysis

Author(s)

Dudas, Patrick M.

Issue Date

2013-02

Keyword(s)

• dark networks
• visualization
• social network analysis
• user-design
• cultural informatics
• social and community informatics
• information retrieval

Abstract

Developing a network based on Twitter data for social network analysis (SNA) is a common task in most academic domains. The need for real-time analysis is not as prevalent due to the fact that researchers are interested in the analysis of Twitter information after a major event or for an overall statistical or sociological study of general Twitter users. Dark network analysis is a specific field that focuses on criminal, terroristic, or people of interest networks in which evaluating information quickly and making decisions from this information is crucial. We propose a platform and visualization called Dynamic Twitter Network Analysis (DTNA) that incorporates real-time information from Twitter, its subsequent network topology, geographical placement of geotagged tweets on a Google Map, and storage for long-term analysis. The platform provides a SNA visualization that allows the user to interpret and change the search criteria quickly based on visual aesthetic properties built from key dark network utilities with a user interface that can be dynamic, up-to-date for time critical decisions and geographic specific.

Publisher

iSchools

Type of Resource

text

Language

en

Permalink

http://hdl.handle.net/2142/39982

DOI

https://doi.org/10.9776/13295

Copyright and License Information

Copyright © 2013 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.

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