According to Wikipedia, Sentiment analysis or opinion mining refers to the application of natural language processing, computational linguistics, and text analytics to identify and extract subjective information in source materials. The rise of social media such as blogs (Blogger, WordPress, TypePad) and social networks (Facebook, LinkedIn, Ning) has fueled interest in sentiment analysis. With the proliferation of reviews, ratings, recommendations and other forms of online expression, online opinion has turned into a kind of virtual currency for businesses looking to market their products, identify new opportunities and manage their reputations. As businesses look to automate the process of filtering out the noise, understanding the conversations, identifying the relevant content and actioning it appropriately, many are now looking to the field of sentiment analysis.
For example, if you are considering buying an Apple iPad, you can check latest Twitter sentiment (positive, negative or neutral) towards the product using online Twitter Sentiment site as below:
iPad Twitter Sentiment
Gadgets powered by Google
Other sites that offer such similar applications are:
1. TweetFeel – Tweetfeel monitors positive and negative feelings in twitter conversations about stuff like movies, musicians, TV shows and popular brands.
2. Twendz – Twitter-mining Web application uses the power of Twitter Search, highlighting conversation themes and sentiment of the tweets that talk about topics you are interested in.
3. PeopleBrowsr – PeopleBrowsr engages the collective intelligence in real-time conversation, identify top influencers, search cross network and see multiple accounts across social streams.
4. groubal – it tracks the customer dissatisfaction of hundreds of brands through social media. A customer satisfaction index built using a Bayesian classifier. Claims 90% accuracy.
5. Brandcrown – it ranks popular brands.
6. OpinionCrawl – online sentiment analysis for current events, companies, products, and people.
7. Tweet Sentiment – attempts to find a correlation between Twitter sentiment and stock prices.
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