Student research opportunities
Social Text Mining for Blogs, Tweets and Facebook
Project Code: CECS_44
This project is available at the following levels:
Honours, Summer Scholar, Masters, PhD
Keywords:
Text Mining; Opinion Mining; Sentiment Mining; Information Retrieval; Natural Language Processing; Social Group Analysis; Blogs; Tweets; Facebook
Supervisor:
Dr Scott SannerOutline:
A fast-growing topic of interest in text analytics is the automatic mining of topics, opinions and sentiment from social communities like the blogosphere, tweets, and Facebook. "What do Australians think about the Kyoto protocol?", "What are the different groups of opinion on this topic?", "What are brief summaries of these opinions?" Wouldn't it be great if we had automated algorithms to answer these questions given the mass of content freely available to us on the web?
Goals of this project
At your fingertips will be state-of-the-art Java tools for web content extraction, information retrieval, and natural language progressing. The goal of this project will be to use these tools and produce a small demonstrator that can automatically extract information to answer such questions as the given examples above. The application may be standalone or may integrate into a website, e.g., a Facebook App.
Requirements/Prerequisites
Good coding skills in Java.
Background Literature
See the web pages of Jure Leskovec and Bing Liu for research related to this project.
