A Machine Learning Approach For Emotions Classification

1388 Words Oct 2nd, 2015 6 Pages
A machine learning approach for emotions classification in Micro blogs

ABSTRACT Micro blogging today has become a very popular communication tool among Internet users. Millions of users share opinions on different aspects of life every day. Therefore micro blogging web-sites are rich sources of data for opinion mining and sentiment analysis. Because micro blogging has appeared relatively recently, there are a few research works that are devoted to this topic.In this paper, we are focusing on using Twitter, which is an amazing microblogging tool and an extraordinary communication medium for text and social web analyses.We will try to classify the emotions in to 6 basic discrete emotional categories such as anger, disgust, fear, joy, sadness and surprise.
Keywords :
Emotion Analysis; Sentiment Analysis; Opinion Mining; Text Classification
1. INTRODUCTION
Sentiment analysis or opinion mining is the computational study of opinions, sentiments and emotions expressed in text. Sentiment analysis refers to the general method to extract subjectivity and polarity from text.It uses a machine learning approach or a lexicon based approach to analyse human sentiments about a topic..The challenge for sentimental analysis lies in identifying human emotions expressed in these text.
The classification of sentiment analysis goes as follows: Machine Learning is the field of study that gives computer the ability to learn without being explicitly programmed. Machine learning explores the…
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