A system and method for determining sentiment of natural language text content in a domain independent manner is provided. The method comprises providing an adjective-polarity database having stored therein a list of adjectives and corresponding polarity values. The method further comprises receiving natural language text content related to a first domain with information about corresponding sentiment. The method further comprises identifying nouns and adjectives in the received tagged natural language text content. The method further comprises associating the polarity value to each of the adjectives identified in the received tagged natural language text content. The method further comprises masking the identified nouns and adjectives in the received tagged natural language text content with part-of-speech tags. The method further comprises utilizing the masked natural language text content for training of a model for determining a sentiment score for natural language text content related to a second domain.
METHOD AND SYSTEM FOR DETERMINING SENTIMENT OF NATURAL LANGUAGE TEXT CONTENT