Browsing by Subject "BlogVox"
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Item BlogVox: Learning Sentiment Classifiers(AAAI, 2007-07-22) Martineau, Justin; Java, Akshay; Kolari, Pranam; Joshi, Anupam; Finin, Tim; Mayfield, JamesPerforming 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.Item BlogVox: Separating Blog Wheat from Blog Chaff(2007-01-07) Java, Akshay; Kolari, Pranam; Finin, Tim; Mayfield, James; Joshi, Anupam; Martineau, JustinBlog posts are often informally written, poorly structured, rife with spelling and grammatical errors, and feature non-traditional content. These characteristics make them difficult to process with standard language analysis tools. Performing linguistic analysis on blogs is plagued by two additional problems: (i) the presence of spam blogs and spam comments and (ii) extraneous non-content including blog-rolls, link-rolls, advertisements and sidebars. We describe techniques designed to eliminate noisy blog data developed as part of the BlogVox system - a blog analytics engine we developed for the 2006 TREC Blog Track. The findings in this paper underscore the importance of removing spurious content from blog collections.