Social Network Data Mining Using Natural Language Processing and Density Based Clustering

被引：7

作者：

Khanaferov, David ^{[1
]}

Luc, Christopher ^{[1
]}

Wang, Taehyung ^{[1
]}

机构：

[1] Calif State Univ Northridge, Dept Comp Sci, Northridge, CA 91330 USA

来源：

2014 IEEE INTERNATIONAL CONFERENCE ON SEMANTIC COMPUTING (ICSC) | 2014年

关键词：

data mining; social network; clustering; NLP; sentiment analysis;

D O I：

10.1109/ICSC.2014.48

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：250 / 251

页数：2