Dynamic Domain Specific Sentimental Word Identification

Query driven sentiment analysis is a difficult problem because the strength and polarity of sentimental word and expressions is dependent upon the topic. This necessitates a dynamic approach fast enough to operate at run time.

In this talk I will outline the problem by presenting new experiments supporting the claim that topical sentiment is expressed by the sum of a large number of very weak signals. As a partial solution I will present a fast, statistically grounded technique to determine sentimental word orientation for a given topic. Then I will present preliminary results using document synthesis to bootstrap topical sentiment polarity classifiers at run time.