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CSAT: Citation Sentiment Analysis Tool

Supervised By:
Imran Ihsan
Duration:
2016 - 2017
Client:
Award:
First Prize Winner - AirTech 2016
Team:
Completed:
Project completed in 100%.
Methodology for Sentiment Analysis
High Frequency Verb Cloud
High Occurrence Verbs in 3 Sentiments
Application Interface

Project description

An Application to find the sentiment of a citation text.

CSAT is a Citation Sentiment Analysis Tool that takes two way path to find the sentiment polarity of a citation. In one direction it uses standard nGram Sentiment Analysis algorithms along with Porter Stemmer and Text Blob. And in second direction it uses Ontology based approach. By extracting verbs from a citation after applying Stemming, Lemmatization and POSTagger, the system creates a weighted match with CCRO Ontology to determine its sentiment polarity. CSAT uses ACL Anthology Network AAN Citation Dataset to create a visualization of both techniques using RDF based Citation Graph.

Tools and Technologies

Project tag