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Sentiment analysis refers to the use of natural language processing toidentify and extract subjective information from textual resources. Oneapproach for sentiment extraction is using a sentiment lexicon. A sentimentlexicon is a set of words associated with the sentiment orientation that theyexpress. In this paper, we describe the process of generating a general purposesentiment lexicon for Persian. A new graph-based method is introduced for seedselection and expansion based on an ontology. Sentiment lexicon generation isthen mapped to a document classification problem. We used the K-nearestneighbors and nearest centroid methods for classification. These classifiershave been evaluated based on a set of hand labeled synsets. The final sentimentlexicon has been generated by the best classifier. The results show anacceptable performance in terms of accuracy and F-measure in the generatedsentiment lexicon.

LexiPers: An ontology based sentiment lexicon for Persian