Analyzing User Reviews of Mobile Applications using Natural Language Processing

The proposed project is to research and develop a user review analysis system for mobile games using machine learning and natural language processing techniques. Traditionally, user review analyses are done by humans, which is inefficient and relatively slow. The project will involve research in the specific areas of topic modeling, sentiment analysis and opinion spam detection. The result of the research will be developed into a deliverable solution. One use of the review analysis system is to retrieve valuable information for the game development team in order to improve the game. It can also be used as a competitive intelligence tool to identify strength and weaknesses of competing products. EA All Play, the partner organization, is expected to be able to extract information about a given mobile game in an efficient and timely way.

Faculty Supervisor:

Dr. Graeme Hirst

Student:

Yunxing (Henry) Zhang

Partner:

Electronic Arts

Discipline:

Computer science

Sector:

Media and communications

University:

University of Toronto