Data Mining Techniques for Sentiment Analysis Social Media Networking Using Different Information Resources

Sentiment analysis Social Media networking with the help of different resources of information in the last decade has gained extraordinary attention. This is credited to the affordability of accessing social network sites such as Twitter, Google, Facebook and additional Social Network sites through the Internet and the web 2.0 technologies. Many people are flattering interested in and relying on Social Media for information and opinion of other users on diverse subject matters. It is significant to translate sentiment expressed by Social Media users to helpful information using data mining techniques. This underscores the importance of data mining techniques on Social Media. Data mining techniques are capable of treatment various research issues with Social Media data which are size, voice and dynamism. This dissertation reviews data mining techniques now in use on Analysing Social Media networking and looked at other data mining techniques that can be careful in the field. Social Media sites are commonly known for information dissemination, opinion/sentiment expression and product reviews. News alerts, breaking news, political debates and Government policy are also discussed and analysed on SOCIAL MEDIA sites. However, while some opinions on SOCIAL MEDIA assist users and other entities to make useful decisions, some are mere assertions and therefore misleading. Users’ opinions/sentiments on SOCIAL MEDIA such as Twitter, Facebook, YouTube and Yahoo are basically positive, negative or neutral (neutral being commonly regarded as no opinion expressed). Online opinions can be discovered using traditional methods but this is conversely inadequate considering the large volume of information generated on all SOCIAL MEDIA sites.