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This week Topsy Labs Inc. released a report claiming its model was able to predict a drop in Netflix's share price after it decided to split its DVD rental and streaming video services by tracking phrases like "just canceled my Netflix subscription."

It's arguable whether investors really needed a sophisticated sentiment measuring analyses to predict Netflix's shares would drop after what has been called the worst business decision since the introduction of "new" Coke in 1985. But social media sentiment analysis is growing more sophisticated and may soon become a key component investors look at before making a decision to buy or sell stock.

Big data and sentiment analysis can do amazing things, whether it's in the enterprise or in the quest to create compelling applications and experiences for consumers. But can technology trends such as these actually predict major real-world events?

As sci-fi as it may sound, that's exactly what researcher Kalev Leetaru was able to accomplish with a little help from SGI's Altix UV supercomputer packing 8.2 teraflops of processing power. Leetaru, a digital media analytics expert at the University of Illinois, wrote software that can scan over 100 million news articles and uses sentiment analysis, text geocoding and predictive analytics to determine when political upheaval will go from rowdy to revolutionary.

Big data and sentiment analysis can do amazing things, whether it's in the enterprise or in the quest to create compelling applications and experiences for consumers. But can technology trends such as these actually predict major real-world events?

As sci-fi as it may sound, that's exactly what researcher Kalev Leetaru was able to accomplish with a little help from SGI's Altix UV supercomputer packing 8.2 teraflops of processing power. Leetaru, a digital media analytics expert at the University of Illinois, wrote software that can scan over 100 million news articles and uses sentiment analysis, text geocoding and predictive analytics to determine when political upheaval will go from rowdy to revolutionary.

Online content is published so fast and furious these days that no one can read it all. Ears are burning at corporate brands, too, because much of that Web content is talking about them. What are people saying? One part of answering that question is to ask how people seem to be feeling about the things they are talking about. Scalable, automated, accurate, sophisticated sentiment analysis is a much sought-after technology that almost no one has really nailed yet.

Jennifer Zeszut was the founder and CEO of Scout Labs, a social media monitoring service acquired by social CRM company Lithium in 2010. ScoutLabs does sentiment analysis, among other things, and Zeszut spoke at the O'Reilly Strata Summit on Big Data this week about the things her company has done that she believes point toward the future of this red hot tech trend.

Researchers at Pennsylvania State University recently revealed the results of a study which looked into how people were using Twitter to talk about products. Companies, of course, fear what a negative barrage of tweets can do to their brand, leading many to establish Twitter accounts themselves to provide information, customer service, and support. As it turns out, these businesses may not need to worry too much about what the "Twitter effect" can do to their image after all. The study revealed that the number of brand-related tweets where sentiment is expressed is not the dominating force that you may think. In fact, the majority of tweets mentioning a brand are merely casual comments or tweets from someone giving or seeking information. And when sentiment is expressed, it's generally positive.

ContextSense is a newly launched sentiment extraction technology from Wingify, a company focused on website optimization solutions. As a part of their core product which helps website owners identify visitor demographics and behavior, target ads, and optimize landing pages, ContextSense demonstrates how Wingify's contextual targeting technology works. To use the tool, you simply enter in a URL or a piece of text, and it will then reveal the overall sentiment of the website (positive or negative), relevant tags, concepts, categories, and contextually similar links. The end result is a quick glimpse into what a site is all about.

The New York Times has an article today about sentiment analysis, a trend which has been accelerating on the back of the Real-time Web - and Twitter in particular. Sentiment analysis is no short-term hot trend. It will eventually become a key feature of search engines, which will integrate the aggregate sentiment of the crowd into search results.

The NY Times article looked at 3 sentiment analysis tools: Scout Labs, The Financial Times' Newssift, and Jodange. It also mentioned 3 Twitter apps: Tweetfeel, Twendz and Twitrratr. In our post we take a look at five other examples of how sentiment analysis is starting to ramp up on the Web. We invite you to add more examples in the comments.

Semantic search engine Evri can now understand how the web feels with the launch of their new sentiment web API. While busy scouring the net for people, places, and things and determining the relationships between them, the search engine is now able to understand the feelings associated with these entities, too, be them positive or negative. Using the API, developers can build applications for things like market intelligence, market research, sports and entertainment, brand management, product reviews and more.