Identifying Your Representative Work Based on Credit Allocation
Peng Bao, Jiahui Wang · 2018
With the rapid development of scientific impact quantification in the field of science of success, the ability to identify the representative work of a researcher has important implications in a wide range of areas, including hiring, funding, and promotion systems. In this paper, we propose a two-step credit allocation algorithm (TSCA) for identifying the representative work of a researcher. This algorithm explicitly captures the importance of a paper, its relevance to other papers, and the unequally distributed contribution of each citation. We validate TSCA by applying it on the citation data from American Physical Society (APS) in the scenario of identifying the Nobel prize winning papers of the Nobel laureates. Experiments demonstrate that the proposed algorithm can significantly outperform the existing methods.