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- 42 creator andy-moniz.
- 42 creator franciska-de-jong.
- 42 type InProceedings.
- 42 label "42".
- 42 sameAs 42.
- 42 abstract "Prior studies highlight the merits of integrating Linked Data to aid investors’ analyses of company financial disclosures. Non-financial disclosures, including reporting on a company’s environmental footprint (corporate sustainability), remains an unexplored area of research. One reason cited by investors is the need for domain knowledge from earth science to interpret such disclosures. To address this challenge, we employ a fully-automated system which employs a Latent Dirichlet Allocation (LDA) model for the discovery of earth science topics in corporate sustainability text. The LDA model is seeded with a vocabulary generated by terms retrieved via a SPARQL endpoint. The terms are seeded as lexical priors into the LDA model. An ensemble tree combines the resulting topic probabilities and classifies the quality of sustainability disclosures using domain expert ratings published by Google Finance. From an applications stance, our results may be of interest to investors seeking to incorporate sustainability considerations into their investment decisions.".
- 42 hasAuthorList authorList.
- 42 title "Analysis of companies’ non-financial disclosures: Ontology learning by topic modeling".