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|Title:||Twitter Sentimental Analysis System|
|Keywords:||Sentimental Analysis;Twitter;Classification;Naive Bayes, SVM, MAximum Entropy;CSED|
|Abstract:||Internet has become important part of in everyone’s life. It is basically useful for user to share their views and opinion in a very short time .Sentimental analysis means extracting important information from user’s views. It extract user’s opinion posted on sites and micro blogging sites and web form by the user .Thus the extracted information is helpful in decision making process. Sentimental analysis is not a simple process, it is very difficult to exactly predict the sentimental from the text, but there are many challenges in performing sentimental analysis. The thesis work that is focused on implementation of system based on sentimental analysis. Features are used to extract the sentimental words and computing frequency of each occurring words. This system uses the twitter posts as raw data. It is used to classify sentiment of each tweet. Then it uses the classification algorithm of machine learning algorithm to classify these words. The polarity of each sentiment word is predicated based on these models.|
|Appears in Collections:||Masters Theses@CSED|
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