research-article

Emotion detection in Roman Urdu text using machine learning

Authors:

Mirza Omer BegAuthors Info & Claims

ASE '20: Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering

Pages 125 - 130

https://doi.org/10.1145/3417113.3423375

Published: 22 January 2021 Publication History

Abstract

Emotion detection is playing a very important role in our life. People express their emotions in different ways i.e face expression, gestures, speech, and text. This research focuses on detecting emotions from the Roman Urdu text. Previously, A lot of work has been done on different languages for emotion detection but there is limited work done in Roman Urdu. Therefore, there is a need to explore Roman Urdu as it is the most widely used language on social media platforms for communication. One major issue for the Roman Urdu is the absence of benchmark corpora for emotion detection from text because language assets are essential for different natural language processing (NLP) tasks. There are many useful applications of the emotional analysis of a text such as improving the quality of products, dialog systems, investment trends, mental health. In this research, to focus on the emotional polarity of the Roman Urdu sentence we develop a comprehensive corpus of 18k sentences that are gathered from different domains and annotate it with six different classes. We applied different baseline algorithms like KNN, Decision tree, SVM, and Random Forest on our corpus. After experimentation and evaluation, the results showed that the SVM model achieves a better F-measure score.

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https://doi.org/10.1109/TCSS.2022.3228649
Tyagi SSzénási S(2024)Exploring the Potential of Convolutional Neural Networks in Sequential Data Analysis: A Comparative Study with LSTMs and BiLSTMs2024 IEEE 22nd World Symposium on Applied Machine Intelligence and Informatics (SAMI)10.1109/SAMI60510.2024.10432861(000243-000248)Online publication date: 25-Jan-2024
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Deshmukh S(2024)Review of Databases used for Text Based Emotion Detection2024 MIT Art, Design and Technology School of Computing International Conference (MITADTSoCiCon)10.1109/MITADTSoCiCon60330.2024.10575618(1-5)Online publication date: 25-Apr-2024
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Index Terms

Emotion detection in Roman Urdu text using machine learning
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing

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cover image ACM Conferences

ASE '20: Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering

September 2020

195 pages

ISBN:9781450381284

DOI:10.1145/3417113

General Chair:
John Grundy,
Program Chairs:
Claire Le Goues,
David Lo

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 22 January 2021

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ASE '20: 35th IEEE/ACM International Conference on Automated Software Engineering

September 21 - 25, 2020

Virtual Event, Australia

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Overall Acceptance Rate 82 of 337 submissions, 24%

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Cited By

Khurana YGupta SSathyaraj RRaja S(2024)RobinNet: A Multimodal Speech Emotion Recognition System With Speaker Recognition for Social InteractionsIEEE Transactions on Computational Social Systems10.1109/TCSS.2022.322864911:1(478-487)Online publication date: Feb-2024
https://doi.org/10.1109/TCSS.2022.3228649
Tyagi SSzénási S(2024)Exploring the Potential of Convolutional Neural Networks in Sequential Data Analysis: A Comparative Study with LSTMs and BiLSTMs2024 IEEE 22nd World Symposium on Applied Machine Intelligence and Informatics (SAMI)10.1109/SAMI60510.2024.10432861(000243-000248)Online publication date: 25-Jan-2024
https://doi.org/10.1109/SAMI60510.2024.10432861
Deshmukh S(2024)Review of Databases used for Text Based Emotion Detection2024 MIT Art, Design and Technology School of Computing International Conference (MITADTSoCiCon)10.1109/MITADTSoCiCon60330.2024.10575618(1-5)Online publication date: 25-Apr-2024
https://doi.org/10.1109/MITADTSoCiCon60330.2024.10575618
Chutia TBaruah N(2024)Emotion Recognition in Assamese Text Using LSTM2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT61001.2024.10724457(1-7)Online publication date: 24-Jun-2024
https://doi.org/10.1109/ICCCNT61001.2024.10724457
Majeed AImtiaz UNseem MAleem MShahzad WBeg MMujtaba H(2024)Extracting emotion from resource poor language through transfer learningMultimedia Tools and Applications10.1007/s11042-024-19870-wOnline publication date: 30-Jul-2024
https://doi.org/10.1007/s11042-024-19870-w
Chutia TBaruah N(2024)A review on emotion detection by using deep learning techniquesArtificial Intelligence Review10.1007/s10462-024-10831-157:8Online publication date: 11-Jul-2024
https://doi.org/10.1007/s10462-024-10831-1
Oyebode OOgubuike RDaniel DOrji R(2024)Emotion Detection from Real-Life Situations Based on Journal Entries Using Machine Learning and Deep Learning TechniquesIntelligent Systems and Applications10.1007/978-3-031-47724-9_32(477-502)Online publication date: 19-Apr-2024
https://doi.org/10.1007/978-3-031-47724-9_32
Aziz SSarfraz MUsman MAftab MRauf H(2023)Geo-Spatial Mapping of Hate Speech Prediction in Roman UrduMathematics10.3390/math1104096911:4(969)Online publication date: 14-Feb-2023
https://doi.org/10.3390/math11040969
Golovnin OPleshanov DStolbova A(2023)Data mining for public channels and groups in telegram messenger2nd International Conference on Computer Applications for Management and Sustainable Development of Production and Industry (CMSD-II-2022)10.1117/12.2669231(9)Online publication date: 5-Jan-2023
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Ashraf SRehman FSharif HKirn HArshad HManzoor H(2023)Fake Reviews Classification using Deep Learning2023 International Multi-disciplinary Conference in Emerging Research Trends (IMCERT)10.1109/IMCERT57083.2023.10075156(1-8)Online publication date: 4-Jan-2023
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