| Title |
The construction of environmental-policy-enterprise knowledge graph based on PTA model and PSA model |
| ID_Doc |
19527 |
| Authors |
Wang, XY; Meng, LZ; Wang, XT; Wang, Q |
| Title |
The construction of environmental-policy-enterprise knowledge graph based on PTA model and PSA model |
| Year |
2021 |
| Published |
|
| DOI |
10.1016/j.rcradv.2021.200057 |
| Abstract |
The environmental policies released by the environmental protection departments cast a profound impact on the production and development of industries and their belonging enterprises, and the activities of individual firms have been paid more and more attention under the economic and social background. Also, since the effectiveness of the environmental policies on enterprises is often postponed, predicting the impact of environmental policies on individual firms has always been a difficult and vital problem. In recent years, many studies have proposed various models to evaluate the influence of environmental policies. However, most models can only analyze the impact of one single environmental policy at the industrial level instead of the enterprise level, which is insufficient to solve the problem. This study builds an environmental-policy-enterprise knowledge graph to automatically predict the impact of multiple ecological policies on different enterprises, and the prediction of the influence can be accurate to one specific firm. Based on deep learning and text processing, this paper constructs the Policy Text Analysis (PTA) model and Policy Sentiment Analysis (PSA) model to obtain the influence scores of multiple policies on enterprises, realizing the automatic prediction of the environmental policy impact. The final prediction accuracy and recall rate is up to 89.64% and 99.12%, indicating that it can provide an accurate method to predict the influence of multiple environmental policies on relevant enterprises. |
| Author Keywords |
Environmental-policy-enterprise knowledge graph; Enterprise level; Automatic prediction model |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Emerging Sources Citation Index (ESCI) |
| EID |
WOS:001107593900003 |
| WoS Category |
Environmental Sciences |
| Research Area |
Environmental Sciences & Ecology |
| PDF |
https://doi.org/10.1016/j.rcradv.2021.200057
|