CSAT: Citation Sentiment Analysis Tool

First Prize in AirTech 2016 - Project Exhibition and Competition
Project Logo
Project Facts
Area: Semantic Web, NLP, Sentiment Analysis
Supervisor: Imran Ihsan
Team: Osama Ahmed Tahir, Ali Jasim Bukhari, Waleed Khalid
For: Air University, Islamabad
Status: Completed
Tools & Technologies
Microsoft .NET Framework,
C#, Python,
Stanford Core NLP,
Lemma Sharp,
Metro Framework
Project Abstract
An Ontology based sentiment analysis using Natural Language Processing and Computational Linguistics on Scholarly Big Data.
A scientific paper contains valuable information about scholarly activity and its evolution. A citation has the potential to reveal important and interesting information about a particular scholarly research. Most of the techniques available today on citation analysis are somewhat based on the principal of number of citations. Citation Content Analysis (CCA) is a technique to analyze citation meaning from the nature of academic writing itself. Citation Sentiment Analysis aims to determine the sentiment polarity that the citation context carries towards the cited paper. The categories of sentiment polarity could be either positive, negative or neutral.
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 Ontology for Citation Reasons – OCR to determine its sentiment polarity.
CSAT uses ACL Anthology Network – AAN Citation Dataset that contains 310 Research Papers and 8736 citations and creates a visualization of both techniques and stores it in an RDF based Citation Graph.
Project Interface
Project Poster
  • Research & Development 90%
  • Project Management 80%
  • Client Communication 80%
  • Team Management 85%
  • Microsoft Project and Visio 80%
  • GUI Design 90%
  • Web & Mobile Application 95%
  • CMS Design & Development 85%
  • HTML 5 90%
  • CSS 3.0 90%
  • PHP / MySQL 90%
  • JS / JQuery 85%
  • JAVA 60%
  • C# / ASP.NET 50%
  • SQL 95%
  • C++ 90%
  • XML / XML Schema 90%
  • XPath / XQuery 90%
  • RDF / RDFs 90%
  • SPARQL 80%
  • OWL 80%