Canadá
This paper seeks to identify sentiment and non-sentiment bearing hashtags by com- bining existing lexical resources. By using a lexicon-based approach, we achieve 86.3% and 94.5% precision in identifying sentiment and non-sentiment hashtags, respectively. Moreover, results obtained from both of our classification models demonstrate that using combined lexical, emotion and word resources is more effective than using a single resource in identifying the two types of hashtags.
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