research-article

Toward a Sentiment Analysis Framework for Social Media

Authors:

Bousselham El Haddaoui,

Raddouane Chiheb,

Abdellatif El AfiaAuthors Info & Claims

LOPAL '18: Proceedings of the International Conference on Learning and Optimization Algorithms: Theory and Applications

Article No.: 29, Pages 1 - 6

https://doi.org/10.1145/3230905.3230919

Published: 02 May 2018 Publication History

Abstract

Nowadays, opinions and sentiments can be easily expressed through social media and have a strong social impact. Thus, the need for an automated way to analyze the generated data with less human effort and more accuracy. In this respect, sentiment analysis tasks such as; preprocessing, classification, etc. provides various techniques that achieves notable accuracy scores, but presents limitations depending on the experimental context.

Through our literature review, only few studies focused on establishing a reference framework for sentiment analysis. In this paper, we provide a literature review for common sentiment analysis tasks with discussion about future research trends, then we propose an abstraction model of a generic framework architecture for sentiment analysis in the context of social media based on previous works and enhanced with new concepts.

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Cited By

El Haddaoui BChiheb RFaizi REl Afia A(2022)On the Sensitivity of LSTMs to Hyperparameters and Word Embeddings in the Context of Sentiment AnalysisProceedings of the 5th International Conference on Big Data and Internet of Things10.1007/978-3-031-07969-6_40(529-542)Online publication date: 3-Jul-2022
https://doi.org/10.1007/978-3-031-07969-6_40
Tanantong TSanglerdsinlapachai NDonkhampai U(2020)Sentiment Classification on Thai Social Media Using a Domain-Specific Trained Lexicon2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)10.1109/ECTI-CON49241.2020.9158329(580-583)Online publication date: Jun-2020
https://doi.org/10.1109/ECTI-CON49241.2020.9158329
Kathuria AGupta ASingla R(2020)A Review of Tools and Techniques for Preprocessing of Textual DataComputational Methods and Data Engineering10.1007/978-981-15-6876-3_31(407-422)Online publication date: 20-Aug-2020
https://doi.org/10.1007/978-981-15-6876-3_31
Show More Cited By

Index Terms

Toward a Sentiment Analysis Framework for Social Media
1. Computing methodologies
  1. Artificial intelligence
  2. Machine learning
    1. Machine learning approaches
2. Information systems
  1. Information retrieval

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LOPAL '18: Proceedings of the International Conference on Learning and Optimization Algorithms: Theory and Applications

May 2018

357 pages

ISBN:9781450353045

DOI:10.1145/3230905

Copyright © 2018 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: 02 May 2018

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LOPAL '18

LOPAL '18: Theory and Applications

May 2 - 5, 2018

Rabat, Morocco

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LOPAL '18 Paper Acceptance Rate 61 of 141 submissions, 43%;

Overall Acceptance Rate 61 of 141 submissions, 43%

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Cited By

El Haddaoui BChiheb RFaizi REl Afia A(2022)On the Sensitivity of LSTMs to Hyperparameters and Word Embeddings in the Context of Sentiment AnalysisProceedings of the 5th International Conference on Big Data and Internet of Things10.1007/978-3-031-07969-6_40(529-542)Online publication date: 3-Jul-2022
https://doi.org/10.1007/978-3-031-07969-6_40
Tanantong TSanglerdsinlapachai NDonkhampai U(2020)Sentiment Classification on Thai Social Media Using a Domain-Specific Trained Lexicon2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)10.1109/ECTI-CON49241.2020.9158329(580-583)Online publication date: Jun-2020
https://doi.org/10.1109/ECTI-CON49241.2020.9158329
Kathuria AGupta ASingla R(2020)A Review of Tools and Techniques for Preprocessing of Textual DataComputational Methods and Data Engineering10.1007/978-981-15-6876-3_31(407-422)Online publication date: 20-Aug-2020
https://doi.org/10.1007/978-981-15-6876-3_31
Zarra TChiheb RFaizi REl Afia A(2018)MOOCs' Recommendation Based on Forum Latent Dirichlet AllocationProceedings of the 2nd International Conference on Smart Digital Environment10.1145/3289100.3289115(88-93)Online publication date: 18-Oct-2018
https://dl.acm.org/doi/10.1145/3289100.3289115

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