Rodríguez Aguilar, Román
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Rodríguez Aguilar, Román
Official Name
Rodríguez Aguilar, Román
Alternative Name
rrodrigueza
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ORCID
Scopus Author ID
56717663000
Researcher ID
AAO-6158-2020

Research Output
Now showing 1 - 10 of 56
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Sentiment Analysis Model on Twitter About Video Streaming Platforms in Mexico

2021 , Rodríguez Aguilar, Román

This work addresses the analysis of the content of the comments on Twitter in the period from December 2020 to February 2021 on the video streaming platforms in Mexico: Netflix, Disney+ and Prime Video. The analysis involves the extraction of comments on Twitter, cleaning the text and the development of a supervised support model for Text Mining for the sentiment classification of tweets in the categories: Positive, Negative or Neutral (spam); as well as the use of resampling techniques to measure the variability of the model’s performance and improve the precision of its parameters. The result allows the measurement of user satisfaction levels and the detection of the most dissatisfied and liked aspects of the platforms. Finally, a business intelligence dashboard was developed in Power BI for the interactive visualization of the results under different information filters. The results show that there is a large percentage of Neutral tweets (spam) that refer mainly to advertising about new releases. Netflix’s satisfaction level is the highest compared to the rest of the platforms due to the liking for its original series, variety, and dynamism of launches; on the contrary, the most unpleasant aspect is removing content from your catalog. For its part, Disney+ has satisfaction lower due to the limited variety of its catalog and the expense involved. In the case of Prime Video, lower levels of satisfaction are observed for removing content from its catalog and for paying more than one platform per month. The application of this methodology could benefit in measurement of satisfaction levels, understanding, decision-making and monitoring of new strategies implemented by the platforms.

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Optimization Methods, Mobile Networks and Data Analytics: Applications in Engineering and Industry 4.0 : Editorial

2020 , Marmolejo Saucedo, José Antonio , Martínez Ríos, Félix Orlando , Rodríguez Aguilar, Román

The business world is changing and demands the integration of various engineering techniques to make the operation of the system in general more efficient. Optimization, information security and a prospective business vision is essential for companies to be more productive. The application of new technological solutions to manufacturing and management processes is one of the ways through which digital transformation in the supply chain advances, on the road to industry 4.0. To achieve this, optimization techniques, soft-computing, machine learning and Big Data technologies must be combined. With this integration it is possible to work with real-time sensed data to build and simulate Digital Twins with very high precision. © Springer Nature

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Designing a resilient supply chain: An approach to reduce drug shortages in epidemic outbreaks

2020 , Lozano-Díez, José Antonio , Marmolejo Saucedo, José Antonio , Rodríguez Aguilar, Román

Introduction: Supply network design is a long-studied topic that has evolved to address disruptive situations. The risk of supply chain disruption leads to the development of resilient supply chains that are capable of reacting effectively. Objectives: In the context of public health, drug supply networks face shortage challenges in many situations, such as current epidemic outbreaks such as COVID-19. Drug shortages can occur due to manufacturing problems, lack of infrastructure, and immediate reaction mechanisms. Methods: The case study is solved with anyLogistix optimization and simulation software. RESULTS: We present the results of a hypothetical study on the impact of COVID-19 on a regional supply network. The results of this research are intended to be the basis for the design of resilient supply chains in epidemic outbreaks. Conclusión: Drug providers should consider strategies to prevent or reduce the impact of shortages as well as disruption spreads. ©2020 José Antonio Lozano Díez, José Antonio Marmolejo Saucedo & Roman Rodríguez Aguilar, licensed to European Alliance for Innovation.

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Financial risk of increasing the follow-up period of breast cancer treatment currently covered by the Social Protection System in Health in México

2018 , Rodríguez Aguilar, Román , Marmolejo Saucedo, José Antonio , Tavera-Martínez, Sonia

Background: The objective of this work is to estimate the financial impact of increasing the monitoring period for breast cancer, which is financed by the Sistema de Protección Social en Salud (SPSS—Social Protection System in Health). Methods: A micro-simulation model was developed to monitor a cohort of patients with breast cancer, and also an estimation was made on the probability of surviving the monitoring period financed by the SPSS. Using the Monte Carlo simulation, the maximum expected cost was estimated to broaden such monitoring. Morbimortality information of the Ministry of Health and cases of breast cancer treated by the SPSS were used.

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Electric Vehicles as Distributed Micro Generation Using Smart Grid for Decision Making: Brief Literature Review

2022 , Sanchez-García, Julieta , Rodríguez Aguilar, Román , Marmolejo Saucedo, José Antonio

This article deals with a brief review of the literature about the potential use of renewable energies through the integration of smart grids and the use of electric vehicles as micro generators that allow energy exchange with the grid. The main technical aspects are addressed, as well as potential benefits and requirements necessary for said integration. Highlighting key aspects in the integration of smart grids, energy storage systems, prosumers and their interaction with electrical vehicles on the grid. © Springer Nature

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Text Mining and Statistical Learning for the Analysis of the Voice of the Customer

2020 , Andrade González, Rosalía , Rodríguez Aguilar, Román , Marmolejo Saucedo, José Antonio

This paper analyzes the content of texts through a Text Mining classification model for the particular case of the Tweets made about the Miniso brand in Mexico during the period from November 17 to 24, 2018. The analysis involves the extraction of the data, the cleaning of the text and supervised support models for high-dimensional data, obtaining as a result the classification of the tweets in the topics: Positive, Negative, Advertising or Requirements of new Branches. As well as the use of resampling techniques to measure the variability of the performance of the model and to improve the accuracy of the parameters. This practice allows to reduce time spent reading texts, especially in Social Networks, finding faster and more efficient trends that help decision-making and respond quickly to customer demand. © 2020, Springer Nature Switzerland AG.

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Correction to: Data Analysis and Optimization for Engineering and Computing Problems

2020 , Vasant, Pandian , Litvinchev, Igor , Marmolejo Saucedo, José Antonio , Rodríguez Aguilar, Román , Martínez Ríos, Félix Orlando

This book was inadvertently published without updating the following (or with the following error) © Springer Nature Switzerland AG 2020

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The Importance of Health and Social Protection Assets in the Economic Welfare of Households in Mexico

2023 , De la Torre-Diaz, Lorena , Rodríguez Aguilar, Román , Rivas Aceves, Salvador

This paper seeks determines how the possession of health and social protection assets affects the probability of a household belonging to a given quintile of a proposed asset ownership index. An ordered logistic regression model was constructed. As a dependent variable, the quintile of each household was used according to the index. This research is based on 48 explanatory variables from the 2020 National Income and Expenses Survey. It confirms that health and social protection assets are relevant in the location of households in a quintile according to its socioeconomic condition. Estimated marginal effects and predictions for every quintile, show that the effect of the assets varies according to the quintile. Ownership of specific assets increase the likelihood of belonging to the higher quintiles. The possession of a voluntary pension fund is the most relevant asset. The empirical results obtained may contribute to design more efficient inequality-reducing public policies by promoting its acquisition and thereby encouraging social mobility. Main limitations of this research are related with the small number of health and social-protection related variables in the survey. ©Revista Mexicana de Economía y Finanzas

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Selecting the Distribution System using AHP and Fuzzy AHP Methods

2024 , Saucedo-Martínez, Jania Astrid , Salais-Fierro, Tomás Eloy , Rodríguez Aguilar, Román , Marmolejo Saucedo, José Antonio

In this research, we present a supporting tool for decision making by designing a distribution system for a trading company of supplies for the welding industry in Mexico. The case study encompasses a distribution system with shortage problems and poor fleet capacity. To address these problems, improvement options were grouped into three possible scenarios through a third-party logistics (3PL) service. Furthermore, for the evaluation and selection of one of the scenarios, the Analytic Hierarchy Process (AHP) methodology was proposed integrating fuzzy logic as a tool for decision making, including factors of uncertainty and subjectivity as well as a comparison with traditional AHP obtaining the best scenario, meeting the requirements of the company, and showing potential improvements in the desired service level for its distribution system. © 2024 Springer Nature

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Estimation of the Stochastic Volatility of Oil Prices of the Mexican Basket: An Application of Boosting Monte Carlo Markov Chain Estimation

2021 , Marmolejo Saucedo, José Antonio , Rodríguez Aguilar, Román

The volatility of the returns on financial assets is not a constant number over time as many valuation models, mainly derivatives, developed during the 80's, assume. The complexity of non-heteroscedasticity and the difference in results when estimated with different methodologies such as historical, implicit or stochastic calculation, make this subject too extensive a field to be covered in this work. However, stochastic volatility has been widely accepted in recent years. Monte Carlo Markov Chain (MCMC) method is explained and used to estimate the distribution of oil prices of Mexican basket as a stochastic variable. MCMC in the univariate case, supposes that we can estimate the distribution of a latent (hidden) variable through the behavior of another variable observed posteriori with the help of Bayesian inference; this method allows an efficient inference independent of the underlying process through an algorithm. The results show a correct adjustment of stochastic volatility to the behavior of the oil prices. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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