The model that we created is a tool to analyse sentiment from the given text. The sentiment analysis is a text mining technique to extract, identify and study the polarity of a given text or document. The results show whether the emotion conveyed in the document is positive, or negative. In principle, the accuracy of a sentiment analysis system is determined by how well it finds similarity with human judgments. This is usually calculated by different measures based on precision and recall over the two target variables of negative and positive texts.
From a business point of view, the output of the data could be utilised for various purposes. This could be for political campaigns, social crisis management or purely for business related goals. Some of the benefits of sentiment analysis in real world are:
• Sentiment Analysis in BI setup is a key application. Based on the reviews generated through sentiment analysis in business, you can always adjust to the present market situation and satisfy your customers in a better way.
• Knowing the sentiment data of your competitors gives you the opportunity as well as the incentive to perk up your performance.
• The tone and temperament of customers experience data can be detected and then categorized according to the sentiments attached. This helps to know what is being properly implemented with regards to products, services and customer support and what needs improvement.
• The polarity of the tweeters towards a particular government can be used to predict the election result