DocumentCode
1787461
Title
Social Network Data Mining Using Natural Language Processing and Density Based Clustering
Author
Khanaferov, David ; Luc, Christopher ; Taehyung Wang
Author_Institution
Dept. of Comput. Sci., California State Univ., Northridge, CA, USA
fYear
2014
fDate
16-18 June 2014
Firstpage
250
Lastpage
251
Abstract
There is a growing need to make sense of all the raw data available on the Internet, hence, the purpose of this study is to explore the capabilities of data mining algorithms applied to social networks. We propose a system to mine public Twitter data for information relevant to obesity and health as an initial case study. This paper details the findings of our project and critiques the use of social networks for data mining purposes.
Keywords
data mining; medical administrative data processing; natural language processing; pattern clustering; social networking (online); density based clustering; health information; natural language processing; obesity information; public Twitter data mining; social network data mining; Cleaning; Clustering algorithms; Data mining; Natural language processing; Semantics; Twitter; NLP; clustering; data mining; sentiment analysis; social network;
fLanguage
English
Publisher
ieee
Conference_Titel
Semantic Computing (ICSC), 2014 IEEE International Conference on
Conference_Location
Newport Beach, CA
Print_ISBN
978-1-4799-4002-8
Type
conf
DOI
10.1109/ICSC.2014.48
Filename
6882032
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