Proceedings of the 2014 International Conference on Management Science and Management Innovation

Word Polarity Analysis Method Based on Topic Model

Authors
Xiao-Nan Fan, Shi-Min Wang
Corresponding Author
Xiao-Nan Fan
Available Online June 2014.
DOI
https://doi.org/10.2991/msmi-14.2014.19How to use a DOI?
Keywords
Word polarity, LDA model, Random Walk, Positive and negative orientation.
Abstract
Along with the proliferation of new media, the user generated content becomes irreplaceable and providing main channel of daily information for people. By get rid of the shackle of the poor information, information technology has entered a big data era. Faced with the data overload, words polarity analysis research appeals the attention of numerous scholars and becomes the important role in national security and information filtering for Internet users, enterprises, and governments. However, due to the rapid change of internet words, the lexicon based sentiment analysis method shows its drawback. Because the traditional method cannot get the polarity of internet words to make the ideal corpus, they usually generate the bad results. This paper presented a topic-based word polarity analysis method which utilizes the LDA topic model and random walk method to get the polarity of a new word. Experiments show that our method achieves the proper accuracy and reasonable results.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2014 International Conference on Management Science and Management Innovation (MSMI 2014)
Part of series
Advances in Economics, Business and Management Research
Publication Date
June 2014
ISBN
978-94-6252-015-8
ISSN
2352-5428
DOI
https://doi.org/10.2991/msmi-14.2014.19How 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  - Xiao-Nan Fan
AU  - Shi-Min Wang
PY  - 2014/06
DA  - 2014/06
TI  - Word Polarity Analysis Method Based on Topic Model
BT  - 2014 International Conference on Management Science and Management Innovation (MSMI 2014)
PB  - Atlantis Press
SN  - 2352-5428
UR  - https://doi.org/10.2991/msmi-14.2014.19
DO  - https://doi.org/10.2991/msmi-14.2014.19
ID  - Fan2014/06
ER  -