Authors:
Manuela Angioni
and
Franco Tuveri
Affiliation:
CRS4, Center of Advanced Studies and Research and Development in Sardinia, Italy
Keyword(s):
Sentiment Analysis, Opinion Mining, NLP, Text Categorization, Semantic Disambiguation.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Natural Language Processing
;
Pattern Recognition
;
Symbolic Systems
Abstract:
The pervasive diffusion of social networks as common way to communicate and share information is becoming a valuable resource for analysts and decision makers. Reviews are used every day by common people or by companies who need to make decisions. It is evident that even the opinion monitoring is essential for listening to and taking advantage of the conversations of possible customers in a decision making process. Opinion Mining is a way to analyse opinions related to specific topics: products, services, tourist locations, etc. In this paper we propose an automatic approach to the extraction of feature terms, applying our experience in the semantic analysis of textual resources to Opinion Mining task and performing a contextualisation by means of semantic categorisation, and by a set of qualities associated to the sense expressed by adjectives and adverbs.