DocumentCode :
3360061
Title :
Emotion detection from “the SMS of the internet”
Author :
Nagarsekar, Uma ; Mhapsekar, Aditi ; Kulkarni, Parag ; Kalbande, D.R.
Author_Institution :
Dept. of Comput. Eng., Univ. of Mumbai, Mumbai, India
fYear :
2013
fDate :
19-21 Dec. 2013
Firstpage :
316
Lastpage :
321
Abstract :
Due to the sudden eruption of activity in the social networking domain, analysts, social media as well as general public are drawn to Sentiment Analysis domain to gain invaluable information. In this paper, we go beyond basic sentiment classification (positive, negative and neutral) and target deeper emotion classification of Twitter data. We have focused on emotion identification into Ekman´s six basic emotions i.e. JOY, SURPRISE, ANGER, DISGUST, FEAR and SADNESS. We have employed two diverse machine learning algorithms with three varied datasets and analyzed their outcomes. We show how equal distribution of emotions in training tweets results in better learning accuracies and hence better performance in the classification task.
Keywords :
Bayes methods; behavioural sciences computing; classification; emotion recognition; learning (artificial intelligence); social networking (online); support vector machines; Ekman six basic emotions; Internet; SMS; SVM; Twitter data; anger; classification task; disgust; emotion classification; emotion detection; emotion distribution; emotion identification; fear; joy; learning accuracies; machine learning algorithms; naive Bayes; negative sentiment classification; neutral sentiment classification; positive sentiment classification; sadness; sentiment analysis domain; social media; social networking domain; support vector machine; surprise; Accuracy; Classification algorithms; Computers; Feature extraction; Support vector machines; Training; Twitter; Naïve Bayes; SVM; emotion identification; machine learning; natural language processing; tweets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computational Systems (RAICS), 2013 IEEE Recent Advances in
Conference_Location :
Trivandrum
Print_ISBN :
978-1-4799-2177-5
Type :
conf
DOI :
10.1109/RAICS.2013.6745494
Filename :
6745494
Link To Document :
بازگشت