[1H1-GS-11] AI and Society: news / arguments

[1H1-GS-11-01] Using news articles to identify emerging trends in Net-Zero societies related to technologies, policy and regulatory

〇Ken Mohri¹, Takeshi Kasuga², Jin Narumiya², Hisanaga Oba¹, Kazuho Sekimoto¹ (1. Deloitte Touche Tohmatsu LLC, 2. Japan Bank for International Cooperation)

Keywords:Net-zero, SDGs, topic modeling, BERT embeddings, Natural Language Processing (NLP)

Efforts to realize a carbon-free society are becoming the minimum requirement for business continuity. With regard to ESG investment, which is an investment that evaluates corporate environmental efforts that are attracting worldwide attention these days. Research on evaluation methods for benchmarks that evaluate opportunities for new profit generation is becoming active. With this activation of ESG investment, information disclosure regarding decarbonization has led to the trust of the market and has begun to be directly linked to corporate value.Therefore, in this study, we visualized the relative progress of each decarbonized topic in each country. Specifically, articles related to decarbonization were extracted from about 40 million articles over the past three years, BERT embedded vectors were clustered for the articles, and characteristic words for each cluster were extracted using c-TF-IDF. From this study, it was found that the efforts for decarbonization are in contrast in Europe, the United States, China and Japan.