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Broadband wireless Communication, Advanced Computing Architectures, Embedded Systems
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Emotion can be expressed in many ways, such as face
expression and gestures, speech and written text. The detection of emotions
from text documents is essentially a content-based classification, which used the
concept of Natural Language programming (NLP) domains. In this paper, an
overview of emotion recognition especially from the text document is discussed.
The paper also described different techniques used for the classification of
emotions. The work done by various researcher using different techniques along
with the output measured is discussed.
[1]. Agrawal, A., &
An, A. (2012, December). Unsupervised emotion detection from text using
semantic and syntactic relations. In Proceedings of The 2012 IEEE/WIC/ACM
International Joint Conferences on Web Intelligence and Intelligent Agent
Technology-Volume 01 (pp. 346-353). IEEE Computer Society.
[2]. Kao, E. C. C., Liu,
C. C., Yang, T. H., Hsieh, C. T., & Soo, V. W. (2009, April). Towards
text-based emotion detection a survey and possible improvements. In 2009
International Conference on Information Management and Engineering (pp.
70-74). IEEE.
[3]. Canales, L., &
Martínez-Barco, P. (2014). Emotion detection from text: A survey. In Proceedings
of the Workshop on Natural Language Processing in the 5th Information Systems
Research Working Days (JISIC) (pp. 37-43).
[4]. Danisman, T., &
Alpkocak, A. (2008, April). Feeler: Emotion classification of text using vector
space model. In AISB 2008 Convention Communication, Interaction and Social
Intelligence (Vol. 1, p. 53).
[5]. Sailunaz, K.,
Dhaliwal, M., Rokne, J., & Alhajj, R. (2018). Emotion detection from text
and speech: a survey. Social Network Analysis and Mining, 8(1), 28.
[6]. Jayakrishnan, R.,
Gopal, G. N., & Santhikrishna, M. S. (2018, January). Multi-class emotion
detection and annotation in malayalam novels. In 2018 International Conference
on Computer Communication and Informatics (ICCCI) (pp. 1-5). IEEE.
[7]. Kratzwald, B.,
Ilić, S., Kraus, M., Feuerriegel, S., & Prendinger, H. (2018). Deep
learning for affective computing: Text-based emotion recognition in decision
support. Decision Support Systems, 115, 24-35.
[8]. Agrawal, A., &An, A. (2012,
December). Unsupervised emotion detection from text using semantic and
syntactic relations. In Proceedings of the The 2012 IEEE/WIC/ACM
International Joint Conferences on Web Intelligence and Intelligent Agent
Technology-Volume 01 (pp. 346-353). IEEE Computer Society.
[9]. Binali, H., &Potdar, V. (2010,
April). Computational approaches for emotion detection in text. In 4th
IEEE International Conference on Digital Ecosystems and Technologies (pp.
172-177). IEEE
[10]. Tao, J. (2004). Context based emotion
detection from text input. In Eighth International Conference on Spoken
Language Processing.
[11]. Canales, L., &Martínez-Barco, P.
(2014). Emotion detection from text: A survey. In Proceedings of the
Workshop on Natural Language Processing in the 5th Information Systems Research
Working Days (JISIC).
[12]. Hancock, J. T., Landrigan, C., &
Silver, C. (2007, April).Expressing emotion in text-based communication.
In Proceedings of the SIGCHI conference on Human factors in computing
systems (pp. 929-932). ACM.