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The purpose of this study is to identify the key factors to minimize carbon emission problem. Within this framework, an examination has been made by considering both data mining and fuzzy decision-making techniques. In the analysis process, N-gram methodology is implemented to the abstracts of 1711 studies in the "Sciencedirect" platform and five different indicators are selected. In the proposed decision-making model, firstly, selected criteria are weighted by Spherical fuzzy CRITIC. Secondly, E7 economies are ranked with RATGOS. Thirdly, a sensitivity analysis is performed, and a comparative evaluation is conducted by MAIRCA technique. The most important originality of this proposed model is generating a new technique named RATGOS. In the literature, there are various decision-making models to rank the alternatives. However, lots of researchers criticized these approaches due to some reasons, such as using Euclidean distance by calculating the distances to the negative ideal solutions. Thus, it is seen that there is a need for a new technique that considers geometric mean in proportional concepts. To reach this objective, the RATGOS technique is introduced so that it can be possible to reach more accurate results. The findings indicate that renewable energy usage is the most critical item to overcome carbon emission problem. Therefore, some measures should be taken to increase renewable energy investments. First, governments can offer incentives for renewable energy investments. These incentives may include various incentives such as tax exemptions and low interest loans. Moreover, more research and development works are required for the development of renewable energy technologies. In this way, it can make renewable energy technologies more effective and efficient. For future research directions, an evaluation can be carried out for developed countries because carbon emissions problem also plays a crucial role for the social and economic improvements of these economies. [ABSTRACT FROM AUTHOR]