MYE: Missing Year Estimation in Academic Social Networks
Tom Z. J. Fu, Qiufang Ying, Dah Ming Chiu

TL;DR
This paper introduces algorithms to estimate missing publication years in academic social networks, improving data completeness and accuracy by leveraging citation and authorship relationships.
Contribution
It proposes advanced inference algorithms that extend information propagation, significantly enhancing coverage and accuracy in missing year estimation across different network types.
Findings
Advanced algorithms outperform simple benchmarks in coverage.
Algorithms improve mean absolute error of year estimation.
Effective across citation, authorship, and combined networks.
Abstract
In bibliometrics studies, a common challenge is how to deal with incorrect or incomplete data. However, given a large volume of data, there often exists certain relationships between the data items that can allow us to recover missing data items and correct erroneous data. In this paper, we study a particular problem of this sort - estimating the missing year information associated with publications (and hence authors' years of active publication). We first propose a simple algorithm that only makes use of the "direct" information, such as paper citation/reference relationships or paper-author relationships. The result of this simple algorithm is used as a benchmark for comparison. Our goal is to develop algorithms that increase both the coverage (the percentage of missing year papers recovered) and accuracy (mean absolute error of the estimated year to the real year). We propose some…
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Taxonomy
TopicsComplex Network Analysis Techniques · Advanced Clustering Algorithms Research · Text and Document Classification Technologies
