Abstract
E-commerce has become very popular because of the service provided and the comfort it provides to users but with this comes different advantages and disadvantages which makes users consider other opinions before making a decision to purchase an item. These days sentiment analysis has become one of the important tasks which helps people to express their opinion on products and services being rendered, sentimental analysis is applied in different aspect of the human world which provides polarity in users opinion to others when making a decision. Sentimental analysis provides aid the analysis of reviews and comments to give or provide a summarized polarity percentage on an event or product. In E-commerce sentimental analysis is important because it assists users to make a decision on products on products. This project will be focused on utilizing Naïve bayes algorithm, SVM and Logistic regression to create a recommendation system that recommends the best e-commerce site to buy from.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Jabbar, J., Urooj, I., Junsheng, W., Azeem, N.: Real-time sentiment analysis on e-commerce application. In: Proceedings of the 2019 IEEE 16th International Conference Networking, Sensing Control. ICNSC 2019, pp. 391–396 (2019)
Priyadharsini, R.L., Ponn Felciah, M.L.: Recommendation system in e-commerce using sentiment analysis. Int. J. Eng. Trends Technol. 49(7), 445–450 (2017)
Oliveira, T., Alhinho, M., Rita, P., Dhillon, G.: Modelling and testing consumer trust dimensions in e-commerce. Comput. Human Behav. 71, 153–164 (2017)
Sin, K.Y., Osman, A., Salahuddin, S.N., Abdullah, S., Lim, Y.J., Sim, C.L.: Relative advantage and competitive pressure towards implementation of e-commerce: overview of small and medium enterprises (SMEs). Procedia Econ. Financ. 35, 434–443 (2016)
Özdemir, A., Çam, H.: The importance of e-commerce in terms of local development: a study in Turkey. Int. J. Bus. Manag. Inf. 5(1), 9–16 (2016)
Khan, A.G.: Electronic commerce: a study on benefits and challenges in an emerging economy. Type Double Blind Peer Rev. Int. Res. J. 16(1), 1–5 (2016). Publ. Glob. Journals Inc. Version 1.0
Kumari, N., Singh, S.N.: Sentiment analysis on e-commerce application by using opinion mining. In: Proceedings of the 2016 6th International Conference - Cloud System and Big Data Engineering Confluence 2016, no. 1, pp. 320–325 (2016)
Zhang, S., Zhong, H.: Mining users trust from e-commerce reviews based on sentiment similarity analysis. IEEE Access 7, 13523–13535 (2019)
Sudheer, K., Valarmathi, B.: Real time sentiment analysis of e-commerce websites using machine learning algorithms. Int. J. Mech. Eng. Technol. 9(2), 180–193 (2018)
Mamtesh, M., Mehla, S.: Sentiment analysis of movie reviews using machine learning classifiers. Int. J. Comput. Appl. 182(50), 25–28 (2019)
Behera, R.K., Jena, M., Rath, S.K., Misra, S.: Co-LSTM: convolutional LSTM model for sentiment analysis in social big data. Inf. Process. Manag. 58(1), 102435 (2021)
Chaudhari, V.V., Dhawale, C.A., Misra, S.: Sentiment analysis classification: a brief review. Int. J. Control Theory Appl. 9(23), 447–454 (2016)
Hilden, J.: Statistical diagnosis based on conditional independence does not require it. Comput. Biol. Med. 14(4), 429–435 (1984)
Rajput, R.: Review of sentimental analysis methods using lexicon based approach. Int. J. Comput. Sci. Mobile 5, 159–166 (2016)
Rajput, R.: Review of sentimental analysis methods using lexicon based approach. Int. J. Comput. Sci. Mob. Comput. 5(2), 159–166 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Shaba, M., Roland, A., Simon, J., Misra, S., Ayeni, F. (2022). A Real-Time Sentimental Analysis on E-Commerce Sites in Nigeria Using Machine Learning. In: Abraham, A., et al. Hybrid Intelligent Systems. HIS 2021. Lecture Notes in Networks and Systems, vol 420. Springer, Cham. https://doi.org/10.1007/978-3-030-96305-7_42
Download citation
DOI: https://doi.org/10.1007/978-3-030-96305-7_42
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-96304-0
Online ISBN: 978-3-030-96305-7
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)