Lexicon-enhanced sentiment analysis framework using rule-based classification scheme.

ABSTRACT: With the rapid increase in social networks and blogs, the social media services are increasingly being used by online communities to share their views and experiences about a particular product, policy and event. Due to economic importance of these reviews, there is growing trend of writing user reviews to promote a product. Nowadays, users prefer online blogs and review sites to purchase products. Therefore, user reviews are considered as an important source of information in Sentiment Analysis (SA) applications for decision making. In this work, we exploit the wealth of user reviews, available through the online forums, to analyze the semantic orientation of words by categorizing them into +ive and -ive classes to identify and classify emoticons, modifiers, general-purpose and domain-spe

SUBMITTER: Asghar MZ 

PROVIDER: S-EPMC5322980 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature