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The stock price varies greatly by the action and the emotion of the people involved in it. They are basically interested in profit. The moods of these people are collected from tweets, articles and blogs. The positive and negative moods affect the stock prices. Using Natural Language Processing and Neural Network we will analyze the blogs and tweets and thus investigate the positive and negative moods and sentiments among the investors and purchasers in stock market. By using this code, SentiWordNet which is a lexical resource for opinion mining. Working of SentiWordNet has an extensive data dictionary.NLTK is a leading platform for building Python programs to work with human language data. It provides user friendly interfaces to about 50 corpora and various resources such as WordNet, along with a suite of text processing libraries for distribution, reasoning, analyzing, tagging, parsing, and semantic reasoning. Neural NetworkNeural Network in this method is trained on the basis of features extracted from the Sentiment Classifier.

Analysis of the Stock Movement and Prediction of Price of Gold Silver and Crude Oil