Inclusion in CSR Reports: The Lens from a Data-Driven Machine Learning Model

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review


Inclusion, as one of the foundations in the diversity, equity, and inclusion initiative, concerns the degree of being treated as an ingroup member in a workplace. Despite of its importance in a corporate’s ecosystem, the inclusion strategies and its performance are not adequately addressed in corporate social responsibility (CSR) and CSR reporting. This study proposes a machine learning and big data-based model to examine inclusion through the use of stereotype content in actual language use. The distribution of the stereotype content in general corpora of a given society is utilized as a baseline, with which texts about corporate texts are compared. This study not only propose a model to identify and classify inclusion in language use, but also provides insights to measure and track progress by including inclusion in CSR reports as a strategy to build an inclusive corporate team.
Original languageEnglish
Title of host publicationProceedings of the First Computing Social Responsibility Workshop within the 13th Language Resources and Evaluation Conference
EditorsMingyu Wan, Chu-Ren Huang
PublisherEuropean Language Resources Association (ELRA)
ISBN (Electronic)9791095546894
Publication statusPublished - Jun 2022
EventLanguage Resources and Evaluation Conference 2022 - Palais du Pharo , France
Duration: 20 Jun 202225 Jun 2022


ConferenceLanguage Resources and Evaluation Conference 2022
Abbreviated titleLREC
Internet address


  • corporate social responsibility (CSR) reports
  • inclusion
  • word embeddings
  • baseline
  • big data


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