Research on the Impacts of Quantitative Factors on Sentimental Classification of Weibo of Different Topics

DOI

10.2991/iwmecs-15.2015.79How to use a DOI?

Keywords

Sentimental classification, training set, quantitative factors, Weibo.

Abstract

Different numbers of terms and texts of training set are involved to optimise the performance of sentiment classification for Weibo repost. The experiment utilises CHI-square test to extract terms and uses support vector machine (SVM) to classify the different sentimental categories. By measuring the performance by F1-score for different training sets, the result illustrates the impacts of quantitative factors on the performance and the differences of the impacts between particular topics.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ruoxi Zhang
PY  - 2015/10
DA  - 2015/10
TI  - Research on the Impacts of Quantitative Factors on Sentimental Classification of Weibo of Different Topics
BT  - Proceedings of the 2015 2nd International Workshop on Materials Engineering and Computer Sciences
PB  - Atlantis Press
SP  - 394
EP  - 397
SN  - 2352-538X
UR  - https://doi.org/10.2991/iwmecs-15.2015.79
DO  - 10.2991/iwmecs-15.2015.79
ID  - Zhang2015/10
ER  -