Name
Abstract | ||
|---|---|---|
Microblog has become a daily communication tool in recent years. Researches on microblog have drawn more and more attention. Microblogging emotional classification is a major research of user intent analysis based on User-Generated Content (UGC). This paper focuses on the discrimination on two emotional tendencies: positive and negative. Firstly, the system cleared the noisy elements in the microblog, then extracted the features of the microblog and finally classified the microblog using Support Vector Machine (SVM). Furthermore, we improve the algorithms of feature extraction and weight computing combining dictionary approach and rule based approach. The result of experiment shows that the method is effective. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ASONAM.2014.6921675 | ASONAM |
Keywords | Field | DocType |
ugc,emotional classification,knowledge based systems,weight computing,combining dictionary approach,user-generated content,svm,daily communication tool,emotion recognition,feature extraction,support vector machine,microblogging emotional classification,microblog combining dictionary,sentiment analysis,support vector machines,user intent analysis,dictionaries,data mining,semantics,classification algorithms | Data mining,Rule-based system,Social media,Computer science,Sentiment analysis,Support vector machine,Microblogging,Feature extraction,Clearance,Statistical classification,Semantics | Conference |
ISBN | Citations | PageRank |
978-1-4799-5876-4 | 0 | 0.34 |
References | Authors | |
3 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ding Yuan | 1 | 0 | 0.34 |
| Zhou Yanquan | 2 | 2 | 1.40 |
| Ruifan Li | 3 | 15 | 3.37 |
| Peng Lu | 4 | 126 | 17.62 |