The effect of inflation and the economy during the Pandemic years: A Methodological Proposal for Sentiment Analysis in Python
DOI:
https://doi.org/10.61467/2007.1558.2026.v17i2.1257Keywords:
NLP, sentimen analysis, inflationAbstract
In this work, NLP Natural Language Processing has been used, specifically sentiment analysis for the problem "The effect of inflation and the economy during the pandemic years" using as a database a tweet written between the dates 01 - 01-2020 to 10-11-2022. The objective is to classify tweets as positive, negative and neutral and establish the impact of some factors related to the economy after the Covid-19 pandemic. A prediction was made based on historical data, on how inflation could be modified in the period 2025-2028. This analysis provides a method to track public inflation expectations by tracking opinions from rich network data.
Smart citations: https://scite.ai/reports/10.61467/2007.1558.2026.v17i2.1257
Dimensions.
Open Alex.
References
Banco de México. (2020). Evolución de la inflación en distintos países en el contexto de la pandemia de COVID-19. Contraste Regional CIISDER, 8(16).
Bird, S., Klein, E., & Loper, E. (2009). Natural language processing with Python. O’Reilly Media. https://www.nltk.org/
Centers for Disease Control and Prevention. (2022, August 16). CDC Museum COVID-19 timeline. https://www.cdc.gov/museum/timeline/covid19.html
Detmers, G.-A., Ho, S.-J., & Karagedikli, Ö. (2022). Understanding consumer inflation expectations during the COVID-19 pandemic. Journal of Monetary Economics, 130, 1–16. https://doi.org/10.1016/j.jmoneco.2022.06.002
García Pérez, L. E., & Mendoza Rivera, R. J. (2025). Modelación de expectativas de inflación en México: Una perspectiva mediante inferencia bayesiana. Análisis Económico, 40(104), 29–47. https://analisiseconomico.azc.uam.mx/index.php/rae/article/view/1361
GeeksforGeeks. (2025, July 23). Twitter sentiment analysis on Russia-Ukraine war using Python. https://www.geeksforgeeks.org/twitter-sentiment-analysis-on-russia-ukraine-war-using-python/
GeeksforGeeks. (2025, July 9). Twitter sentiment analysis using Python. https://www.geeksforgeeks.org/python/twitter-sentiment-analysis-using-python/
Instituto Nacional de Estadística y Geografía. (2025). National Consumer Price Index (NCPI): Base second half of July 2018; update of basket and weights 2024. https://www.inegi.org.mx/temas/inpc/
JustAnotherArchivist. (n.d.). snscrape [Software]. https://github.com/JustAnotherArchivist/snscrape
JustAnotherArchivist. (n.d.). snscrape: A Python library for scraping social networking sites. https://github.com/JustAnotherArchivist/snscrape
Loria, S. (n.d.). TextBlob: Simplified text processing [Software]. https://textblob.readthedocs.io/en/dev/
Morales Pelagio, R. C., Robles Ulloa, O., & Mora Gutiérrez, A. A. (2024). Comparación de la inflación-desempleo de Estados Unidos y México al inicio de la pandemia de COVID-19. ACADEMO, 11(3), 261–270. https://doi.org/10.30545/academo.2024.set-dic.5
Muller Durán, N. I. (2022). Impactos económicos del COVID-19 en la inflación (Proyecto PAPIIT IA301621). Universidad Nacional Autónoma de México. http://www.economia.unam.mx/assets/pdfs/econmex/07/03%20Nancy%20Muller.pdf
Nava Olivares, R. (2020). Percepción social de la era post COVID-19. Contraste Regional, 8(16), 57–78.
Pang, B., Lee, L., & Vaithyanathan, S. (2002). Thumbs up? Sentiment classification using machine learning techniques. In Proceedings of the ACL-02 Conference on Empirical Methods in Natural Language Processing (pp. 79–86). Association for Computational Linguistics. https://doi.org/10.3115/1118693.1118704
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 International Journal of Combinatorial Optimization Problems and Informatics

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.