Nouns Speak: A Novel Approach for Noun Sentiment Scoring

Abstract

Measuring human perception can be introduced as one of the most vital mechanisms in today’s world. This is very important in the fields of social media, business decision making, education, military, biological appliances, making political decisions and more. Sentiment scoring is the key technical factor for measuring human perception under natural language processing. The parts of speech are the main factors behind sentiment scoring. Even though there are valid approaches to determine the sentiment score based on adjectives, verbs or adverbs, still there is a demand for a valid noun scoring methodology. Nouns can be introduced as the most neglected part of speech in sentiment scoring. Almost all the existing noun scoring approaches are based on adjective centric or adjective-adverb centric computational methodologies. This paper brings a novel and valid approach to determine the scoring value for nouns. New noun scoring axioms have been introduced based on the degrees of noun; subjective, objective, implicit and explicit. Then using these axioms, novel set of noun sentiment scoring modules have been implemented. These modules have been evaluated using movie corpus as the data domain and the experimental results show promising results.