Text Classification and Analysis with Social Media Platform
Text Classification, Text Mining and Sentiment Analysis have received huge attention, especially because of the availability of large volume of textual data on social media, e commerce websites, blogs and other similar sources. This data is usually unstructured that becomes complex and expensive to extract knowledge from them to make some intelligent decisions. There is a growing need for developing different methodologies and models for efficiently processing the texts and extracting useful information from it. Text analysis, also known as opinion mining, is the process of quantifying the emotional value in a series of words or text, to gain an understanding of the attitudes, opinions and emotions expressed about particular object. One way to extract information is text classification and its analysis that helps in decision making in various field of our lives. One of such a growing field is Social Media. Now a days people are so much active to obtain and share different types of information updates through social media on a 24/7 basis. Many research areas have tried to extract valuable insights from these large volumes of user generated content. This paper performs the study and analysis of Social Media post by using different technique of text analysis and opinion mining along with sentiment analysis. This study will help to identify different techniques, and chose the most suitable one that helps to identify the most efficient to analyses the Social Media post. IndexTerms: Decision Making, Natural Language Processing (NLP) Social Networking, Social Media, Text classification, Text Analysis, Unstructured Data.