Sentimental analysis of female entrepreneurs based on public tweets

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DOI:

https://doi.org/10.29057/jas.v4i8.9579

Keywords:

Sentimental Analysis, Entrepreneurs, Twitter

Abstract

After the declaration of the COVID 19 pandemic, jobs and occupations had to return to normal, however many people lost their main source of resources, so the incorporation of women in different ventures has been a flag to get ahead with work for their families, so the objective of this work is to identify opinions about entrepreneurs,  using the technique of sentimental analysis to classify unstructured information from public tweets using for data processing, the Rstudio software with the retweet, word cloud and emo libraries collecting the feelings that people have through the microblogging platform Twitter in the period from June 20 to July 10, 2022. The results show that 74.53% of users perceive positive and very positive feelings toward women entrepreneurs, so it can be concluded that the impact of the incorporation of women entrepreneurs, which although at this time is still uncertain is perceived as an important factor for the economic recovery.    

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References

OECD (2022), OECD Economic Surveys: Mexico 2022, OECD Publishing, Paris, https://doi.org/10.1787/2e1de26c-en.

Lamba, M., Madhusudhan, M. (2022). Sentiment Analysis. In: Text Mining for Information Professionals. Springer, Cham. https://doi.org/10.1007/978-3-030-85085-2_7.

G. Shobana, B. Vigneshwara, and M. S. A, “Twitter Sentimental Analysis,” no. November 2018, 2019.

Liu, Bing (2010). Sentiment Analysis and Subjectivity. In Indurkhya, N.; Damerau, F. J. (eds.). Handbook of Natural Language Processing (Second ed.)..

C. Kaur and A. Sharma, (2020) EasyChair Preprint Twitter Sentiment Analysis on Coronavirus using Textblob.

DIARIO CONCEPCIÓN (2022) Mujeres Emprendedoras https://www.diarioconcepcion.cl/carta-al-director/2022/07/12/mujeres-emprendedoras.html

INEGI (2021) Estadísticas a propósito del día internacional de la mujer https://www.inegi.org.mx/contenidos/saladeprensa/aproposito/2021/mujer2021_Nal.pdf

AMMJE (2021) Las mujeres quieren ser las protagonistas en la reactivación económica. https://ammje.mx/prensa/articulo.html?id=2

Weston, B. (2018) How and Why Women Start Businesses. https://www.score.org/blog/how-and-why-women-start-businesses

Granados, C (2020) Las Nuevas Emprendedoras de Negocios por Internet, conocidas como “las Nenis” https://www.milenio.com/negocios/nenis-mujeres-llevan-sustento-13-millones-familias.

Garcia, M (2021) Esta es la cara del micro emprendimeiento femenino en Mexico https://emprendedor.com/esta-es-la-cara-del-microemprendimiento-femenino-en-mexico-y-su-transformacion/Marisol García Fuentes

Mathews, S., Bianchi, C., Perks, K., Healy, M.J., & Wickramasekera, R. (2016). Internet marketing capabilities and international market growth. International Business Review, 25, 820-830.

Abd-Alrazaq, A., Alhuwail, D., Househ, M., Hamdi, M., & Shah, Z. (2020). Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study. Journal of medical Internet research, 22(4), e19016.

https://doi.org/10.2196/19016

Natural language toolkit, NLTK Project. Rev. November 5, 2013.http://www.nltk.org

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Published

2023-01-05

How to Cite

Vega-Barrios, A., Álcantara Hernández, R. J., & Duana-Avila, D. (2023). Sentimental analysis of female entrepreneurs based on public tweets. Journal of Administrative Science, 4(8), 14–21. https://doi.org/10.29057/jas.v4i8.9579