Research on the Impacts of Quantitative Factors on Sentimental Classification of Weibo of Different Topics
Available Online October 2015.
- 10.2991/iwmecs-15.2015.79How to use a DOI?
- Sentimental classification, training set, quantitative factors, Weibo.
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.
- © 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 -