Application of text mining to the analysis of climate-related disclosures

Bernal, Ángel Iván Moreno; Caminero, Teresa

doi:10.1016/j.irfa.2022.102307

Cited by 21 publications

(5 citation statements)

References 9 publications

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“…Basically case folding is the simplest and most effective process in text mining [52]. The function of this folding case is to convert all uppercase letters into lowercase letters [53]. The development of case folding can be presented in the Pseudocode 1 algorithm.…”

Section: Case Foldingmentioning

confidence: 99%

Development of natural language processing on morphologybased Minangkabau language stemming algorithm

Sovia

Defit

Yuhandri

et al. 2023

IJEECS

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Minangkabau language (ML) is one of the daily communication tools used by the people of West Sumatra, Indonesia. ML is a challenge in communicating. The ML language translation process is necessary to facilitate communication. This study aims to build a translation system for ML into Indonesian by developing the concept of natural language processing (NLP). NLP development adopts the performance of morphology-based Minangkabau language stemming algorithm (MLSA) which can separate basic words with affixes and endings. The research dataset adopts 600 basic ML words sourced from the big Minangkabau dictionary. The results of this study provide analytic output that can translate ML into Indonesian well. These results are presented based on the testing process on basic word input with an accuracy rate of 97.16% and based on text documents of 91.65%. Thus, the MLSA performance process presents the accuracy of the translation process. Based on these results, this research contributes to developing a stemming algorithm model in carrying out the process of removing prefixes, inserts, and suffixes in the Minangkabau language. Overall, this research can be useful as a tool for translating the ML into Indonesian.

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Section: Case Foldingmentioning

confidence: 99%

Development of natural language processing on morphologybased Minangkabau language stemming algorithm

Sovia

Defit

Yuhandri

et al. 2023

IJEECS

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“…Based on relevant studies and analyses of the impact of climate transition risk on the value of corporate assets [31][32][33][34], this paper mainly analyzes the causes and determinants of corporate fossil energy stranded asset risk and removes the confounding factors that are not related to the transition risk.…”

Section: Empirical Analysismentioning

confidence: 99%

Determinants of Corporate Fossil Energy Assets Impairment and Measurement of Stranded Assets Risk

Zhao,

Wu,

Wen

2023

Energies

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Climate change and transition risks have become major issues concerning the sustainable development of human society today. And the stranded fossil energy assets generated in this context are gradually becoming an important factor affecting corporate development and the stability of financial markets. Based on the data of China’s A-share listed companies in the high-carbon industry from 1998 to 2021, a two-way fixed-effects model is used to study the determinants of corporate fossil energy asset impairment. Furthermore, a “two-stage estimation approach” is used to measure the risk of stranding corporate fossil energy assets The results show that: (1) climate transition risks are a significant cause of stranded corporate fossil energy assets; (2) the stranded risk of Chinese companies’ fossil energy assets has been oscillating upward over the past two decades; (3) the stranded risk has increased significantly after the “double carbon” target. Based on the above conclusions, this paper puts forward relevant suggestions from both government and enterprise perspectives.

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“…Text mining plays a vital role in financial analysis by extracting valuable insights from vast amounts of unstructured textual data, including financial reports, news articles, social media, and analyst reports [4]. Through text preprocessing techniques such as cleaning, tokenization, and removing stopwords, the raw data is refined for analysis.…”

Section: Introductionmentioning

confidence: 99%

Text Mining and Financial Analysis Modeling for Financial Statement Disclosure

Kang

2024

jes

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This paper explores the integration of financial analysis, text mining, and blockchain technology to enhance financial statement disclosure and analysis processes. Leveraging text mining algorithms, the study extracts valuable insights from unstructured financial data, unveiling hidden patterns and sentiments within financial statements. Additionally, blockchain technology is employed to ensure secure and immutable storage of financial data, fostering transparency and trust in financial transactions and disclosures. Through the automation and digitization of financial reporting processes, stakeholders can streamline financial statement analysis, identify risks and opportunities, and make data-driven decisions with greater accuracy and efficiency.

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Application of text mining to the analysis of climate-related disclosures

Cited by 21 publications

References 9 publications

Development of natural language processing on morphologybased Minangkabau language stemming algorithm

Development of natural language processing on morphologybased Minangkabau language stemming algorithm

Determinants of Corporate Fossil Energy Assets Impairment and Measurement of Stranded Assets Risk

Text Mining and Financial Analysis Modeling for Financial Statement Disclosure

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