SwePub
Sök i LIBRIS databas

  Extended search

onr:"swepub:oai:DiVA.org:bth-25993"
 

Search: onr:"swepub:oai:DiVA.org:bth-25993" > Automatic ESG Asses...

  • 1 of 1
  • Previous record
  • Next record
  •    To hitlist
  • Fischbach, JannikNetlight Consulting GmbH, Germany (author)

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

  • Article/chapterEnglish2023

Publisher, publication year, extent ...

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

Numbers

  • 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

Supplementary language notes

  • Language:English
  • Summary in:English

Part of subdatabase

Classification

  • Subject category:ref swepub-contenttype
  • Subject category:kon swepub-publicationtype

Notes

  • [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.

Subject headings and genre

Added entries (persons, corporate bodies, meetings, titles ...)

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

Related titles

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

Internet link

Find in a library

To the university's database

  • 1 of 1
  • Previous record
  • Next record
  •    To hitlist

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Close

Copy and save the link in order to return to this view