Research on the Impacts of Quantitative Factors on Sentimental Classification of Weibo of Different Topics
Authors
Ruoxi Zhang
Corresponding Author
Ruoxi Zhang
Available Online October 2015.
- 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/).
Cite this article
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 -