An Approach to Sentiment Analysis through Deep Learning
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This project mainly aims to analyze the sentiment of a person using Deep Learning. Deep Learning is the latest process to help analyze near-perfect sentiments. It feeds a lot of data to the algorithm and in the process adjusts itself to constantly progress in the prediction process. Sentiment analysis is a type of data mining that measures the proclivity of human opinions through Natural Language Processing (NLP), computational linguistics and text analysis, which are used to extract and analyze subjective information from the Web-mostly social media and similar sources. It is the understandin...
This project mainly aims to analyze the sentiment of a person using Deep Learning. Deep Learning is the latest process to help analyze near-perfect sentiments. It feeds a lot of data to the algorithm and in the process adjusts itself to constantly progress in the prediction process. Sentiment analysis is a type of data mining that measures the proclivity of human opinions through Natural Language Processing (NLP), computational linguistics and text analysis, which are used to extract and analyze subjective information from the Web-mostly social media and similar sources. It is the understanding and arrangement of emotions (positive, negative and neutral) within text data using text analysis techniques.Apart from this, there is a social platform named as Twitter, where people express their views related to various current issues in the form of emotion token as well as symbol. So it becomes a great source to work on, where people having different languages but can express using emotion symbols. The social media has even dark side. Here in this work we also differentiate between fake and original news using sentiment analysis.
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