Emotion Evaluation from Text: A Survey
By: Bader, Aabiroo
.
Contributor(s): Bhat,Amjad Husain.
Publisher: New Delhi STM Journals 2018Edition: Vol 5 (2),May-Aug.Description: 8-20p.Subject(s): Computer EngineeringOnline resources: Click Here
In:
Journal of artificial intelligence research and advances (JoAIRA)Summary: Information extraction is the process of retrieving structured information from unstructured or semi-structured text. It has a wide range of applications in domains such as biomedical literature mining, business intelligence, sentiment analysis, and emotion analysis. This survey describes recent works in the field of emotion detection for text data, being a part of the broader area of affective computing. It has been inspired by the well-known fact that, despite there is much work done in this field of research but the clock of research is still ticking ON. The increment of this work is due to a significant amount of emotional data available on social web. Analyzing this data over the internet means we are spanning across the world, going through all the cultures and communities. This paper summarizes the previous works done in, by the various emotional models and computational approaches employed.
| Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
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Articles Abstract Database
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School of Engineering & Technology Archieval Section | Not for loan | 2021-2021427 |
Information extraction is the process of retrieving structured information from unstructured or semi-structured text. It has a wide range of applications in domains such as biomedical literature mining, business intelligence, sentiment analysis, and emotion analysis. This survey describes recent works in the field of emotion detection for text data, being a part of the broader area of affective computing. It has been inspired by the well-known fact that, despite there is much work done in this field of research but the clock of research is still ticking ON. The increment of this work is due to a significant amount of emotional data available on social web. Analyzing this data over the internet means we are spanning across the world, going through all the cultures and communities. This paper summarizes the previous works done in, by the various emotional models and computational approaches employed.
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