基于主题覆盖范围的可持续发展目标标签系统比较

Li Li, Yu Zhao, Zhesi Shen
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引用次数: 0

摘要

随着可持续发展目标(SDGs)的重要性与日俱增,出现了各种标签系统来进行有效的监测和评估。本研究对 185 万份文档中的六种标签系统进行了纸张和主题层面的评估。我们的研究结果表明,SDGO 和 SDSN 系统更具侵略性,而 Auckland、Aurora、SIRIS 和 Elseviere 等系统则表现出显著的主题一致性,大多数 SDG 的相似度得分都超过了 0.75。然而,论文层面的相似性一般都不高,尤其是像 SDG 10 这样的特定 SDG。我们强调了上下文信息在基于关键词的标注系统中的关键作用,并指出忽略上下文会在检索论文时产生偏差(例如,生物医学和地理上下文之间的 "迁移 "差异)。这些结果揭示了可持续发展目标标注系统之间的巨大差异,强调了改进方法以提高可持续发展目标评估的准确性和相关性的必要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of Sustainable Development Goals Labeling Systems based on Topic Coverage
With the growing importance of sustainable development goals (SDGs), various labeling systems have emerged for effective monitoring and evaluation. This study assesses six labeling systems across 1.85 million documents at both paper level and topic level. Our findings indicate that the SDGO and SDSN systems are more aggressive, while systems such as Auckland, Aurora, SIRIS, and Elsevier exhibit significant topic consistency, with similarity scores exceeding 0.75 for most SDGs. However, similarities at the paper level generally fall short, particularly for specific SDGs like SDG 10. We highlight the crucial role of contextual information in keyword-based labeling systems, noting that overlooking context can introduce bias in the retrieval of papers (e.g., variations in "migration" between biomedical and geographical contexts). These results reveal substantial discrepancies among SDG labeling systems, emphasizing the need for improved methodologies to enhance the accuracy and relevance of SDG evaluations.
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