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  • Fischbach, JannikNetlight Consulting GmbH, Germany (författare)

Automatic ESG Assessment of Companies by Mining and Evaluating Media Coverage Data : NLP Approach and Tool

  • Artikel/kapitelEngelska2023

Förlag, utgivningsår, omfång ...

  • Institute of Electrical and Electronics Engineers (IEEE),2023
  • printrdacarrier

Nummerbeteckningar

  • LIBRIS-ID:oai:DiVA.org:bth-25993
  • https://urn.kb.se/resolve?urn=urn:nbn:se:bth-25993URI
  • https://doi.org/10.1109/BigData59044.2023.10386488DOI

Kompletterande språkuppgifter

  • Språk:engelska
  • Sammanfattning på:engelska

Ingår i deldatabas

Klassifikation

  • Ämneskategori:ref swepub-contenttype
  • Ämneskategori:kon swepub-publicationtype

Anmärkningar

  • [Context:] Society increasingly values sustainable corporate behaviour, impacting corporate reputation and customer trust. Hence, companies regularly publish sustainability reports to shed light on their impact on environmental, social, and governance (ESG) factors. [Problem:] Sustainability reports are written by companies and therefore considered a company-controlled source. Contrarily, studies reveal that non-corporate channels (e.g., media coverage) represent the main driver for ESG transparency. However, analysing media coverage regarding ESG factors is challenging since (1) the amount of published news articles grows daily, (2) media coverage data does not necessarily deal with an ESG-relevant topic, meaning that it must be carefully filtered, and (3) the majority of media coverage data is unstructured. [Research Goal:] We aim to automatically extract ESG-relevant information from textual media reactions to calculate an ESG score for a given company. Our goal is to reduce the cost of ESG data collection and make ESG information available to the general public. [Contribution:] Our contributions are three-fold: First, we publish a corpus of 432,411 news headlines annotated as being environmental-, governance-, social-related, or ESG-irrelevant. Second, we present our tool-supported approach called ESG-Miner, capable of automatically analysing and evaluating corporate ESG performance headlines. Third, we demonstrate the feasibility of our approach in an experiment and apply the ESG-Miner on 3000 manually labelled headlines. Our approach correctly processes 96.7% of the headlines and shows great performance in detecting environmental-related headlines and their correct sentiment. © 2023 IEEE.

Ämnesord och genrebeteckningar

Biuppslag (personer, institutioner, konferenser, titlar ...)

  • Adam, MaxTechnical University of Munich, Germany (författare)
  • Dzhagatspanyan, VictorTechnical University of Munich, Germany (författare)
  • Mendez, DanielBlekinge Tekniska Högskola,Institutionen för programvaruteknik(Swepub:bth)dmz (författare)
  • Frattini, Julian,1995-Blekinge Tekniska Högskola,Institutionen för programvaruteknik(Swepub:bth)juf (författare)
  • Kosenkov, OleksandrFortiss GmbH, Germany (författare)
  • Elahidoost, ParisaFortiss GmbH, Germany (författare)
  • Netlight Consulting GmbH, GermanyTechnical University of Munich, Germany (creator_code:org_t)

Sammanhörande titlar

  • Ingår i:Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023: Institute of Electrical and Electronics Engineers (IEEE), s. 2823-28309798350324457

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