文章基本信息

标题：Indicative assessment method of the public perception of environmental marketing ideas
本地全文：下载
作者：Anna Grabar ; Lyubov Manukhina ; Nataliya Nikonova 等
期刊名称：E3S Web of Conferences
印刷版ISSN：2267-1242
电子版ISSN：2267-1242
出版年度：2021
卷号：244
页码：10023
DOI：10.1051/e3sconf/202124410023
出版社：EDP Sciences
摘要：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.
其他摘要：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.