Multi-Document, Aspect-Based Sentiment Analysis of Political News Articles

The main objective of the project is to upgrade the existing system at Gnowit to create a complex self learning automated decision support system. The system(crawlers) will automatically collect all the data related to any company, political system or a specific entity from the articles, blogs and reviews and create a more actionable report. The system will also check the credibility of the news and perform the controversy analysis. The mined information and knowledge will be saved and used to train a engine which could predict the future events of an entity or object. The system also tries to quantify the sentiment between multiple aspects.

Faculty Supervisor:

Ahmed Lakhssassi

Student:

Aravind Kilaru;Youcef Fouzar

Partner:

Gnowit Inc

Discipline:

Engineering - other

Sector:

Information and cultural industries

University:

Université du Québec en Outaouais