Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)

Text Visualization and LDA Model Based on R Language

Authors
Hongjie Li, Peng Cheng, Huiyang Xie
Corresponding Author
Hongjie Li
Available Online June 2016.
DOI
https://doi.org/10.2991/mecs-17.2017.95How to use a DOI?
Keywords
R Language, Word cloud, community mining, LDA model.
Abstract
On the Internet, text is the mainly form of information generated by users, analyzing the text can get a lot of important information. Therefore, the text analysis has become an important means of dealing with text data. In this study, R is an open-source software, could be used to analyze users of sina Weibo and their comments. In order to find hot topics and dig the internal links in the comments, then constitute the network structure, this study used a variety of R language function package to visualize categorized word and word cloud. The LDA theme model is used to analyze the potential relationships among the entries, and provides a solution for analyzing the users' behaviors and habits in the social network and tracking hot topics.
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This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)
Series
Advances in Engineering Research
Publication Date
June 2016
ISBN
978-94-6252-352-4
ISSN
2352-5401
DOI
https://doi.org/10.2991/mecs-17.2017.95How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Hongjie Li
AU  - Peng Cheng
AU  - Huiyang Xie
PY  - 2016/06
DA  - 2016/06
TI  - Text Visualization and LDA Model Based on R Language
BT  - Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/mecs-17.2017.95
DO  - https://doi.org/10.2991/mecs-17.2017.95
ID  - Li2016/06
ER  -