Automated Estimation of Emotion Analysis On Social Media

Authors(5) :-Bushra Shaikh1, Chaitali Shanbhag2, Sheetal K3, Unnimaya C4, Mrs. Ayesha Taranum5

Social media became popular where in people are willing to share their emotions and opinions or to participate in social networking. Accordingly, the understanding of social media usage became important. The emotion analysis is emerged as one of useful methods to analyze emotional stats expressed in textual data including social media data. However, this method still presents some limitations, particularly with based on accuracy, lexicon and aspect. To overcome and improve this weakness, we propose an automated estimation of emotion analysis in this paper by using the morphological sentence pattern model. Emotion analysis is the process of determining whether a opinion of writing is positive or negative.

Authors and Affiliations

Bushra Shaikh1
Department of information science and engineering, GSSSIETW, Mysuru, Karnataka, India
Chaitali Shanbhag2
Department of information science and engineering, GSSSIETW, Mysuru, Karnataka, India
Sheetal K3
Department of information science and engineering, GSSSIETW, Mysuru, Karnataka, India
Unnimaya C4
Department of information science and engineering, GSSSIETW, Mysuru, Karnataka, India
Mrs. Ayesha Taranum5
Department of information science and engineering, GSSSIETW, Mysuru, Karnataka, India

Emotion Analysis; Natural Language Processing, Social Media, Morphological Sentence Patterns, Aspect Based Approach

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Publication Details

Published in : Volume 4 | Issue 6 | May-June 2018
Date of Publication : 2018-05-08
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 532-537
Manuscript Number : CSEIT184699
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Bushra Shaikh1, Chaitali Shanbhag2, Sheetal K3, Unnimaya C4, Mrs. Ayesha Taranum5, "Automated Estimation of Emotion Analysis On Social Media ", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 4, Issue 6, pp.532-537, May-June-2018.
Journal URL : http://ijsrcseit.com/CSEIT184699

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