BlogVox: Learning Sentiment Classifiers

Authors: Justin Martineau, Akshay Java, Pranam Kolari, Anupam Joshi, Tim Finin, and James Mayfield

Book Title: Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence

Date: July 22, 2007

Abstract: Performing sentiment analysis upon a topic, specified by key words, without prior knowledge about the key words is a difficult task. With the growth of the blogosphere researchers, corporations, and politicians, among others are very interested in applying sentiment detection to blogs. To accommodate the demands from myriad users, with similarly diverse desires, a sentiment analysis engine for blogs must discover domain specific features relevant to queries in order to accurately assess the sentiment of blogs. Using meta-learning upon the results of web searches, as BlogVox does, can accomplish this goal

Type: InProceedings

Publisher: Menlo Park, CA; Cambridge, MA; London; AAAI Press; MIT Press; 1999

Pages: 2

Number: 1888-1889

Volume: 22

Tags: learning and discovery, information retrieval

Google Scholar: s4UiCv0HThMJ

Number of Google Scholar citations: 2 [show citations]

Number of downloads: 790

Available for download as

size: 99554 bytes

Bookmark at: Digg | Del.icio.us | Connotea | CiteULike