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

• Microsoft .NET Framework
• C#
• Python
• GraphViz
• TikkaDotNet
• Stanford Core NLP
• Lemma Sharp
• NLTK
• Metro Framework

Project tag

• Semantic Web
• NLP
• Sentiment Analysis