Abstract | ||
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The present research exploits the large amount of linguistic resources developed into the Lexicon-grammar paradigm in the domain of the Opinion Mining. Grounded on the Semantic Predicates theory, the proposed system is able to automatically match the syntactic structures selected by special classes of verbs, indicating positive or negative Sentiment, Opinion or Physical acts, with the semantic frames evoked by the same lexical items. This methods has been tested on a large dataset composed of short texts, such as tweets and news headings. |
Year | Venue | Field |
---|---|---|
2015 | RANLP | Information retrieval,Computer science,Sentiment analysis,Lexical item,Grammar,Exploit,Lexicon,Software,Artificial intelligence,Natural language processing,Predicate (grammar),Syntax |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
20 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Annibale Elia | 1 | 7 | 4.95 |
Serena Pelosi | 2 | 1 | 5.08 |
Alessandro Maisto | 3 | 2 | 6.82 |
Raffaele Guarasci | 4 | 0 | 2.37 |