Abstract
This research aims to present a fuzzy-logic-based conceptual model for environmental accidents analysis , to reveal corporate social responsibility initiatives by companies responsible for the disasters. We studied one of the biggest environmental man-made disasters in history, the one that occurred on March 24, 1989 in Prince William Sound, Alaska when the oil tanker Exxon Valdez spilled 10.8 million gallons of American crude oil. The data was collected from the online database of the newspaper The New York Times for the timespan 03/24/1989–09/01/2017 . As a central point of the research, we investigate ethical issues based on the mapping of an ethical vocabulary carried out in the corpus of the analyzed documents. The results show that the proposed model can be replicated, after some adjustments, to verify actions in accordance with the principles of corporate social responsibility for other environmental accidents.
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Notes
- 1.
The parameter allows retrieving by relevance criteria or by the most recent publication data or by the oldest published on the NYT platform.
- 2.
The scripts applied in the processing were considered those published in the methodology published on the website https://www.machinelearningplus.com/nlp/topic-modeling-gensim-python/. These were optimized and adapted according to the context of the research data and interests.
- 3.
Data set available at: https://doi.org/10.6084/m9.figshare.13555661.
- 4.
Available at https://doi.org/10.6084/m9.figshare.13567838.
- 5.
Available at https://doi.org/10.6084/m9.figshare.13567871.
- 6.
Due to its multidisciplinary nature, the fuzzy rules-based system is known by several other names, such as “fuzzy rules-based inference system”, “expert fuzzy system”, “fuzzy model” and “controller logical fuzzy”.
- 7.
A linguistic variable is a variable whose values are fuzzy set names. For example, the temperature of a given process can be a linguistic variable assuming low, medium, high, etc. These values can be described by fuzzy sets.
- 8.
For more information about a FRBS, see [1].
- 9.
Triangular-type functions were chosen, as it was the one that presented the best result, according to what was expected in the model.
- 10.
For more information on other defuzzification methods, see [1].
- 11.
Available at https://doi.org/10.6084/m9.figshare.13582988.
- 12.
Available at https://doi.org/10.6084/m9.figshare.13567883.
- 13.
Available at https://doi.org/10.6084/m9.figshare.13583042.
- 14.
Available at https://doi.org/10.6084/m9.figshare.13583081.
- 15.
Available at https://doi.org/10.6084/m9.figshare.13583123.
- 16.
Available at https://doi.org/10.6084/m9.figshare.13583216.
- 17.
Available at https://doi.org/10.6084/m9.figshare.13583555.
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Acknowledgments
We would like to thank professors Mariana Claudia Broens, Jose Arthur Quilici Gonzalez and Maria Eunice Quilici Gonzalez for the helpful supervision and indications during the fundamental stages of this research. This paper was developed with the collaboration of the team of project “Understanding opinion and language dynamics using massive data”, financed by The São Paulo Research Foundation - FAPESP (process number: 2016/50256-0), to whom we thank the opportunity to conduct this research. Ana Claudia Golzio also received support FAPESP (process number: 2019/08442-9) during the development of this paper, and Mirelys Puerta-Díaz received funding from Coordination for the Improvement of Higher Education Personnel (CAPES) - Financial Code 001.
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Golzio, A.C., Puerta-Díaz, M. (2021). A Model for Analysis of Environmental Accidents Based on Fuzzy Logic. In: Bisset Álvarez, E. (eds) Data and Information in Online Environments. DIONE 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 378. Springer, Cham. https://doi.org/10.1007/978-3-030-77417-2_23
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