| Autor: |
Sabeti, Behnam, Hosseini, Pedram, Ghassem-Sani, Gholamreza, Mirroshandel, Seyed Abolghasem |
| Rok vydání: |
2019 |
| Předmět: |
|
| Druh dokumentu: |
Working Paper |
| DOI: |
10.29007/f4j4 |
| Popis: |
Sentiment analysis refers to the use of natural language processing to identify and extract subjective information from textual resources. One approach for sentiment extraction is using a sentiment lexicon. A sentiment lexicon is a set of words associated with the sentiment orientation that they express. In this paper, we describe the process of generating a general purpose sentiment lexicon for Persian. A new graph-based method is introduced for seed selection and expansion based on an ontology. Sentiment lexicon generation is then mapped to a document classification problem. We used the K-nearest neighbors and nearest centroid methods for classification. These classifiers have been evaluated based on a set of hand labeled synsets. The final sentiment lexicon has been generated by the best classifier. The results show an acceptable performance in terms of accuracy and F-measure in the generated sentiment lexicon. |
| Databáze: |
arXiv |
| Externí odkaz: |
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