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A classification algorithm to link official documents to Sustainable Development Goals
KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Sustainability Assessment and Management.
Salvo Nicotra holds a PhD in Computer Science and is a technology teacher at the University of Catania and chief technology officer (CTO) at a tech company focused on Big Data analysis and Artificial Intelligence algorithms. His research interests focus on streaming data mining, sustainability and mass personalisation in marketing..
2024 (English)In: Towards Sustainable Futures: The Role of Evaluation, Informa UK Limited , 2024, p. 166-185Chapter in book (Other academic)
Abstract [en]

The United Nations adopted the Sustainable Development Goals (SDGs) on September 25, 2015, to address a wide range of global challenges and promote sustainable development worldwide. Since its adoption, there has been a growing interest among businesses, organizations, and governments in using the SDGs as a framework for sustainable development. One way this interest has manifested is through an increase in the number of documents and reports published by organizations that mention the SDGs. This happened for several reasons. Many organizations recognize that sustainable development is essential not only for the well-being of society and the planet but also for their long-term success and profitability. In addition, reporting on the SDGs can help organizations communicate their sustainability performance to stakeholders, including customers, employees, investors, and regulators. Investors and stakeholders are increasingly interested in the sustainability performance of companies and organizations. As a result, the number of documents published by companies and organizations mentioning SDGs has grown exponentially. All while their claims far exceed their actual sustainability initiatives. This means that much of the sustainability marketing out there is often overstated. Given all these documents, it is valuable to detect the SDGs they refer to. However, this assessment is difficult and labor-intensive to do manually, mainly when dealing with large organizations or referring to specific economic sectors or national and international public institutions. Therefore, specific algorithms can be used to quantitatively assess the alignment of a document to the SDGs, automatically identifying the extent to which the document mentions the SDGs and the degree to which it aligns with the goals. In this context, this chapter explores and reflects on the possibility of using a classification algorithm to analyze and assess companies’ and organizations’ SDG-related communication profiles. To this end, a recently developed classification algorithm is presented and tested to link text documents to their mentioned SDGs automatically.

Place, publisher, year, edition, pages
Informa UK Limited , 2024. p. 166-185
National Category
Environmental Sciences
Identifiers
URN: urn:nbn:se:kth:diva-346138DOI: 10.4324/9781032714936-11Scopus ID: 2-s2.0-85190932310OAI: oai:DiVA.org:kth-346138DiVA, id: diva2:1855923
Note

QC 20240507

Part of ISBN 9781032714936

Available from: 2024-05-03 Created: 2024-05-03 Last updated: 2024-05-07Bibliographically approved

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Mazzeo Rinaldi, Francesco

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