Comparative Study of Machine Learning Algorithms for Social Media Text Analysis

Abstract

This paper highlights the way different machine learning algorithms are used in analyzing social media text. This is the internet age. People make use of online forums, blogs posts, tweets etc. to communicate with each other. As a result of increased social networking, amount of data generated is enormous. This data is an excellent source of information in all walks of life ranging from business, marketing, trends analysis and prediction etc. Sentiment analysis refers to identification of user-generated text as positive or negative or neutral automatically. This classification of sentiments into classes can be done based on the document, Sentence, Feature or Aspect. This paper presents how machine learning techniques are used for analyzing sentiments expressed on Twitter platform. Comparative study of these machine learning techniques is done for better understanding.