to download project abstract/base paper of naive bayes algorithm


The user emotion analysis has been a great deal, Here primarily, the twitter dataset is used for analysis. [6] In the current trend, twitter application usage is getting drastically increased where people share their thoughts with each other throughout the world. Generally people use social media as a platform to express their opinion to others, In the meantime Facebook and Twitter serve as the major source for them. Hence they make use of this when needed. The volume of the tweets remain quite high since it is a collection of so many tweets throughout the world, and also it consists of both positive and negative tweets, For the purpose of analysis it is necessary to find the positive and negative tweets and categorize them accordingly. In this project the input dataset consists of a compilation of a number of tweets which expresses the thoughts of various people regarding the election results and their own thoughts about different election candidates who compete in the election, correspondingly each person may have varying opinion on each candidate which will be positive or negative. The analysis of these tweets will help in recording a small survey over those different candidates. The dataset consists of more than 2000 records. The analysis is being done with the help of python programming by importing various packages and implementing a number of functions required for analysis. The results are obtained in two different categories namely positive and negative. Multinomial Naive Bayes classifier has been used for the purpose of analysis. The work is further extended and tested for the imdb movie review dataset, mobile review dataset and the results are categorized as positive and negative naive bayes algorithm.

Sentimental Analysis is a broader field in text mining which has a great role in text classification. Twitter Analysis is one of the subareas in Sentimental analysis where the tweets are being classified into different categories, Twitter serves as a source for the society in gathering the people’s thoughts, Often twitter contributes very high in marketing. People share their thoughts regarding various products in the market, which may include the quality of the product, the most current trending product in the market, which marks out a varying graph of the thoughts of different people. Not only in marketing, twitter also has a major effect in many fields, in many cases the tweets of people change the situation.

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