On predictive modeling of the twitter-based sales data using a new probabilistic model and machine learning methods
The term marketing refers to the various strategies employed by a company to enhance the visibility of its brands among potential consumers. Advertising serves as an effective channel for marketing efforts, allowing a company to showcase its products and services to the target audience. Numerous pro...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | Alexandria Engineering Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016824014996 |
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| _version_ | 1825206995070746624 |
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| author | Min Wan Mohammed A. Alshahrani Najla M. Aloraini Alia A. Alkhathami Haifa Alqahtani |
| author_facet | Min Wan Mohammed A. Alshahrani Najla M. Aloraini Alia A. Alkhathami Haifa Alqahtani |
| author_sort | Min Wan |
| collection | DOAJ |
| description | The term marketing refers to the various strategies employed by a company to enhance the visibility of its brands among potential consumers. Advertising serves as an effective channel for marketing efforts, allowing a company to showcase its products and services to the target audience. Numerous probability-oriented strategies have been suggested and carried out to investigate the effectiveness of advertising mechanisms. In accordance with this pivotal portion of the literature, we develop a new probabilistic model called a new cosine inverse Weibull (NCI-Weibull) distribution, which serves to analyze the sales related to advertising on the Twitter platform. The derivation of point estimators is accomplished for the new model. In addition, a simulation study is presented, which is based on the NCI-Weibull distribution. We further illustrate the applicability of the NCI-Weibull distribution through an analysis of Twitter-based sales data and comparing it with various other statistical models. Furthermore, we employ two machine learning techniques to forecast the sales, with a particular emphasis on 1-step and 3-step advance predictions. The statistical analysis indicates that multilayer perceptron (MLP) is superior in the field of short-term forecasting, whereas support vector regression (SVR) is more effective in the context of longer-term predictions. |
| format | Article |
| id | doaj-art-ff5e1f2ae1744813a19fdc9eeb234650 |
| institution | Kabale University |
| issn | 1110-0168 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Alexandria Engineering Journal |
| spelling | doaj-art-ff5e1f2ae1744813a19fdc9eeb2346502025-02-07T04:47:07ZengElsevierAlexandria Engineering Journal1110-01682025-02-01113661671On predictive modeling of the twitter-based sales data using a new probabilistic model and machine learning methodsMin Wan0Mohammed A. Alshahrani1Najla M. Aloraini2Alia A. Alkhathami3Haifa Alqahtani4School of Statistics and Data Science, Jiangxi University of Finance and Economics, Nanchang, Jiangxi, 330013, China; Nanchang Jiaotong Institute, Nanchang, Jiangxi 330100, ChinaDepartment of Mathematics, College of Sciences and Humanities, Prince Sattam Bin Abdulaziz University, Alkharj 11942, Saudi ArabiaDepartment of Mathematics, College of Science, Qassim University, Buraydah 51452, Saudi ArabiaDepartment of Basic Science, College of Science and Theoretical Studies, Saudi Electronic University, Riyadh 11673, Kingdom of Saudi ArabiaDepartment of Statistics and Business Analytics, United Arab Emirates University, Al Ain 15551, Abu Dhabi, United Arab Emirates; Corresponding author.The term marketing refers to the various strategies employed by a company to enhance the visibility of its brands among potential consumers. Advertising serves as an effective channel for marketing efforts, allowing a company to showcase its products and services to the target audience. Numerous probability-oriented strategies have been suggested and carried out to investigate the effectiveness of advertising mechanisms. In accordance with this pivotal portion of the literature, we develop a new probabilistic model called a new cosine inverse Weibull (NCI-Weibull) distribution, which serves to analyze the sales related to advertising on the Twitter platform. The derivation of point estimators is accomplished for the new model. In addition, a simulation study is presented, which is based on the NCI-Weibull distribution. We further illustrate the applicability of the NCI-Weibull distribution through an analysis of Twitter-based sales data and comparing it with various other statistical models. Furthermore, we employ two machine learning techniques to forecast the sales, with a particular emphasis on 1-step and 3-step advance predictions. The statistical analysis indicates that multilayer perceptron (MLP) is superior in the field of short-term forecasting, whereas support vector regression (SVR) is more effective in the context of longer-term predictions.http://www.sciencedirect.com/science/article/pii/S1110016824014996Inverse weibull distributionCosine functionMonte carlo simulationTwitterSaleStatistical modeling |
| spellingShingle | Min Wan Mohammed A. Alshahrani Najla M. Aloraini Alia A. Alkhathami Haifa Alqahtani On predictive modeling of the twitter-based sales data using a new probabilistic model and machine learning methods Alexandria Engineering Journal Inverse weibull distribution Cosine function Monte carlo simulation Sale Statistical modeling |
| title | On predictive modeling of the twitter-based sales data using a new probabilistic model and machine learning methods |
| title_full | On predictive modeling of the twitter-based sales data using a new probabilistic model and machine learning methods |
| title_fullStr | On predictive modeling of the twitter-based sales data using a new probabilistic model and machine learning methods |
| title_full_unstemmed | On predictive modeling of the twitter-based sales data using a new probabilistic model and machine learning methods |
| title_short | On predictive modeling of the twitter-based sales data using a new probabilistic model and machine learning methods |
| title_sort | on predictive modeling of the twitter based sales data using a new probabilistic model and machine learning methods |
| topic | Inverse weibull distribution Cosine function Monte carlo simulation Sale Statistical modeling |
| url | http://www.sciencedirect.com/science/article/pii/S1110016824014996 |
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