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
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;
Conference_Titel :
Semantic Computing (ICSC), 2014 IEEE International Conference on
Conference_Location :
Newport Beach, CA
Print_ISBN :
978-1-4799-4002-8
DOI :
10.1109/ICSC.2014.48