Sunday, August 30, 2009

Sentiment Analysis: Mining the Web for Feelings

I read in The New York Times a nice article about Sentiment Analysis, written by Alex Wright, where he commented about some new sentiment analysis companies that are trying to tap into the growing business interest in what is being said online. "The rise of blogs and social networks has fueled a bull market in personal opinion: reviews, ratings, recommendations and other forms of online expression. An emerging field known as sentiment analysis is taking shape around one of the computer world’s unexplored frontiers: translating the vagaries of human emotion into hard data", he said.

“Social media used to be this cute project for 25-year-old consultants. Now, top executives are recognizing it as an incredibly rich vein of market intelligence”, said Margaret Francis, vice president for product at Scout Labs. “Our algorithm is about 70 to 80 percent accurate,” said Ms. Francis, who added that its users can reclassify inaccurate results so the system learns from its mistakes."

Jodange, another company, uses a sophisticated algorithm that not only evaluates sentiments about particular topics, but also identifies the most influential opinion holders, based on research by computer science professor Claire Cardie.

Newssift uses an experimental program that tracks sentiments about business topics in the news, coupled with a specialized search engine that allows users to organize their queries by topic, organization, place, person and theme. It is used by The Financial Times.

Bo Pang developed software that looks at several different filters, including polarity (is the statement positive or negative?), intensity (what is the degree of emotion being expressed?) and subjectivity (how partial or impartial is the source?). He is researcher at Yahoo, and co-wrote Opinion Mining and Sentiment Analysis, one of the first academic books on sentiment analysis.

“Sentiments are very different from conventional facts,” said Seth Grimes, the founder of Alta Plana, who points to the many cultural factors and linguistic nuances that make it difficult to turn a string of written text into a simple pro or con sentiment. “I see sentiment analysis becoming a standard feature of search engines,” he said, and suggests that such algorithms could begin to influence both general-purpose Web searching and more specialized searches in areas like e-commerce, travel reservations and movie reviews.

With the quick growth of social networks, the use of Sentiment Analysis is becoming increasingly important to get the sentiment right from human emotions and opinions, translating into data to make better decisions.

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