Abstract:
Opinions are one of the basic entities in human conversations. It is in human nature to have feelings and sentiments about the people and the happenings around them. Opinions and beliefs of people around us affect us in determining what choices we make and what do we believe in. Humans generally ask for opinion of other people when they need to make an important decision Many applications like Facebook, Twitter and Messenger such as Whatsapp use text Data Mining and NLP techniques to extract relevant information from user conversations such as Customer reviews, popular news and general opinion of the public on certain topics. They then sell this information to the relevant brands, companies etc. who want to make use of this information. We designed an application tool that can be used to extract useful information like user sentiments, security hazards and Customer Intelligence from the casual user conversations. The general idea is to make the useless natural language conversations useful by picking out only the meaningful information. Once, the information has been extracted, it can be used for different sorts of surveys and analysis. We used text from social media, blogs and news articles for this purpose. We have determined salient features of users like their opinions , sentiments, current trends , their interests and topics which user is talking about most .
