Towards Finding a Research Lineage Leveraging on Identification of Significant Citations. Issue 1 (13th October 2021)

• Record Type: Journal Article
• Authors: Ghosal, Tirthankar; Singh, Muskaan
• Is Part Of: Proceedings of the Association for Information Science and Technology. Volume 58:Issue 1(2021)
• Page Start: 456
• Page End: 460
• Publication Date: 2021-10-13
• Subjects: Citation Significance Detection -- Feature Engineering -- Idea Propagation -- Machine Learning -- Research Lineage; Information science -- Congresses; Information technology -- Congresses; Information science; Information technology; Conference papers and proceedings; 020
• DOI: 10.1002/pra2.478
• Languages: English
• ISSNs: 2373-9231

Abstract

Abstract: Finding the lineage of a research topic is crucial for understanding the prior state of the art and advancing scientific displacement. The deluge of scholarly articles makes it difficult to locate the most relevant prior work and causes researchers to spend a considerable amount of time building up their literature list. Citations play a significant role in discovering relevant literature. However, not all citations are created equal. A majority of the citations that a paper receives are for providing contextual, and background information to the citing papers and are not central to the theme of those papers. However, some papers are pivotal to the citing paper and inspire or stem up the research in the citing paper. Hence the nature of citation the former receives from the latter is significant. In this work in progress paper, we discuss our preliminary idea towards establishing a lineage for a given research via identifying significant citations. We hypothesize that such an automated system can facilitate relevant literature discovery and help identify knowledge flow for at least a certain category of papers. The distal goal of this work is to identify the real impact of research work or a facility beyond direct citation counts.