E3S Web Conf.
Volume 244, 2021XXII International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies (EMMFT-2020)
|Number of page(s)||8|
|Section||Bioeconomy and Low Carbon Development|
|Published online||19 March 2021|
Indicative assessment method of the public perception of environmental marketing ideas
1 Vyatka State University, Moskovskaya, 36, Kirov, 610000, Russia
2 Moscow State University of Civil Engineering, 26, Yaroslavskoye Shosse, 109377, Moscow, Russia
3 Vyatka State Agrotechnological University, Oktyabrsky avenue, 133, Kirov, 610017, Russia
* Corresponding author: firstname.lastname@example.org
Natural Language Processing is a machine learning method based on mathematical linguistics that can identify trends in public opinion. The article analyzes the possibility of implementing LDA and NLP methods to identify the growing public interest to the problems of ecology and environmental conservation. It will provide the basis for manufacturers to make eco-marketing decisions. Reorienting production towards creating green goods, introducing new ecological products to the market, promoting energy-saving technologies requires significant investments. To get a return, it is required to capture the steady demand of contractors and consumers for ecologization. The article offers a comparative analysis of getting information by classical methods (for example, through surveys) and machine learning methods. The most important sources of data collection are highlighted on the basis of their popularity, public attention and the number of individuals participating in the discourse. The author has developed key categories and keywords with which the Russian society associates the perception of environmental marketing. The result of Natural Language Processing is presented to assess public perception of ecological marketing ideas.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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