Sentilo: Frame-Based Sentiment Analysis

Abstract

Sentilo is an unsupervised, domain-independent system that performs sentiment analysis by hybridizing natural language processing techniques and semantic Web technologies. Given a sentence expressing an opinion, Sentilo recognizes its holder, detects the topics and subtopics that it targets, links them to relevant situations and events referred to by it and evaluates the sentiment expressed on each topic/subtopic. Sentilo relies on a novel lexical resource, which enables a proper propagation of sentiment scores from topics to subtopics, and on a formal model expressing the semantics of opinion sentences. Sentilo provides its output as a RDF graph, and whenever possible it resolves holders’ and topics’ identity on Linked Data.