Implementation of a Web System with Machine Learning for Sentiment Analysis in Social Networks for the Marketing
Implementation of a Web System with Machine Learning for Sentiment Analysis in Social Networks for the Marketing |
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| © 2023 by IJETT Journal | ||
| Volume-71 Issue-11 |
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| Year of Publication : 2023 | ||
| Author : Beatriz Ambrosio Santiago, Paul Bravo Macedo, Laberiano Andrade-Arenas |
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| DOI : 10.14445/22315381/IJETT-V71I11P205 | ||
How to Cite?
Beatriz Ambrosio Santiago, Paul Bravo Macedo, Laberiano Andrade-Arenas, "Implementation of a Web System with Machine Learning for Sentiment Analysis in Social Networks for the Marketing," International Journal of Engineering Trends and Technology, vol. 71, no. 11, pp. 45-55, 2023. Crossref, https://doi.org/10.14445/22315381/IJETT-V71I11P205
Abstract
This research work aims to implement a web system that uses Machine Learning through sentiment analysis in social networks for the marketing area of the company D'Onofrio. The main objective is to apply sentiment analysis techniques to identify the opinions and needs of consumers and to increase the effectiveness of marketing tactics and the decision-making process. The methodology employed combines natural language processing tools and machine learning algorithms to analyze user-created content on social media platforms. Relevant data on perceptions and emotions associated with the D'Onofrio brand and consumer preferences and demands will be collected. The legal framework will be based on the laws and regulations applicable in the Peruvian context, ensuring that privacy and personal information safeguarding requirements are met. The results of this study will provide valuable information to the company D'Onofrio about consumer perceptions on social networks, allowing for more informed decision-making in implementing effective marketing strategies tailored to the target audience's needs. In conclusion, the application of machine learning through sentiment analysis in social networks represents a promising opportunity to improve consumer understanding and strengthen the relationship between the company and its audience.
Keywords
Sentiment analysis, Machine learning, Web System, DMAIC, Kanban.
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