Sentiment Analysis Using Common-Sense and Context Information

Sentiment analysis research has been increasing tremendously in recent times due to the wide range of business and social applications. Sentiment analysis from unstructured natural language text has recently received considerable attention from the research community. In this paper, we propose a novel sentiment analysis model based on common-sense knowledge extracted from ConceptNet based ontology and context information. ConceptNet based ontology is used to determine the domain specific concepts which in turn produced the domain specific important features. Further, the polarities of the extracted concepts are determined using the contextual polarity lexicon which we developed by considering the context information of a word. Finally, semantic orientations of domain specific features of the review document are aggregated based on the importance of a feature with respect to the domain. The importance of the feature is determined by the depth of the feature in the ontology. Experimental results show the effectiveness of the proposed methods

Računalnolingvistička analiza korisničkih komentara na internetskim portalima

U rujnu 2013. godine prikupili smo korisničke komentare s tri hrvatska internetska portala (jutarnji.hr, net.hr i bitno.net) na temu prikupljanja potpisa za referendum o braku. Komentari su nastali u periodu od 12. do 26. svibnja 2013. godine. Na tim komentarima obavili smo nekoliko računalnolingvističkih analiza – analizu sentimenata, analizu polarnih frazi i analizu jezika korištenog u komentarima. Analize su pokazale da su komentari na portalima mahom negativni i prema sentimentu i prema polarnim frazama (najpozitivniji su na katoličkom portalu bitno.net), a na portalima jutarnji.hr i net.hr statistički značajnima su se pokazale razlike između ukupnog sentimenta komentara i sentimenta prema inicijativi (što je sentiment prema inicijativi pozitivniji, pozitivniji je i ukupni sentiment komentara). Također, statistički značajnom se pokazala i razlika između ukupnog sentimenta i jezika korištenog u komentarima (što je sentiment prema inicijativi pozitivniji, jezik komentatora je standardniji). Kada je riječ o korištenom jeziku, oko 50% svih komentara pisano je nestandardnim jezikom, s mnogo vulgarizama.In September 2013 we collected users' comments on three Croatian news websites (jutarnji.hr, net.hr i bitno.net), made on articles about collecting signatures for a marriage referendum in Croatia. Comments were made between 12 May 2013 and 26 May 2013. We then conducted several computational linguistics analyses (sentiment analysis, polarity analysis and language analysis) on those comments. Results showed that comments on websites are mostly negative, with mostly negative sentiments and many negative polar words, phrases and sentences (the most positive website is Catholic website bitno.net). When it comes to quantitative analysis of sentiments and language, we found that there are statistically significant differences between general sentiment in comments and sentiment towards the initiative (the more positive sentiment towards the initiative, the more positive genral sentiment) and between general sentiment and language used in comments (the more positive general sentiment, the more standard the language). When it comes to language analysis, we found that around 50% of all comments was written in non-standard language variety, with many vulgarisms