Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/2765
Title: Text-Based Analysis of Emotion by Considering Tweets
Authors: Sailunaz, Kashfia
Özyer, Tansel
Rokne, Jon
Alhajj, Reda
143116
Keywords: Computer science
artificial intelligence
computer science
information systems
computer science
interdisciplinary applications
Issue Date: May-2018
Publisher: Springer Verlag Wien
Source: Sailunaz, K., Özyer, T., Rokne, J., & Alhajj, R. (2018). Text-Based Analysis of Emotion by Considering Tweets. In Machine Learning Techniques for Online Social Networks (pp. 219-236). Springer, Cham.
Abstract: People express their emotions in various ways, including facial expression, gesture, speech, speech frequency, writing, etc. In today's world where almost every person interacts with other people via social networking and social media, the emotional state of a person can be determined by analyzing the text collected from his/her posts and comments. Although emotion extraction and analysis from text posted in social networks and social media like facebook, twitter, etc. is a very challenging task, still it can give researchers a valuable insight into the complexity of human emotions. In this paper, test from tweets has been used for detecting 32 primary human emotions and then the emotions were analyzed against gender, location, and temporal information of the considered people.
URI: https://link.springer.com/chapter/10.1007/978-3-319-89932-9_11
https://hdl.handle.net/20.500.11851/2765
ISBN: 9783319899329
9783319899312
ISSN: 2190-5428
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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