Sentiment analysis is the name given to extracting and quantifying positive and negative reactions from text. Netvibes includes vocabulary analysis that detects positive and negative sentiment words. This level of semantic tagging can then be used as part of the decision making process in a business process when it is rendered visible.
Along with the informational side of text, there is an emotive side in some cases. People freely express their emotions about a product or a company in online forums and blogs. Sentiment analysis is the name given to extracting and quantifying positive and negative reactions from text.
Thanks to Exalead CloudView, Netvibes can capture the voice of your customers. Text is analyzed by comparing each word to a list of positively oriented words (for example, fantastic, superb, good, excellent, clever,…) and to a list of negatively oriented words (for example, disgusting, dirty, stupid, disappointing, depressing, …).
The presence of negation (for example, not good) changes the orientation of a word. Some words may have a higher weight than others (e.g., hilarious is stronger than funny). A calculation involving the weights and orientation of the effect-bearing words determines whether a text passage is positive or negative. When an entity has been identified in the passage, it is affected by the overall tone. Sentiment analysis over large quantities of text is relatively easy, once the basic vocabulary has been marked with its semantic orientation.
For manual tagging, the user has the ability to apply color coding for defining the nature of sentiment (positive, negative, neutral, SWOT analysis) and use additional keyword tags.