Discipline Reputation Evaluation Based on PhD Exchange Network

TL;DR

This paper introduces a novel method for evaluating discipline reputation using social network analysis of PhD exchange networks, providing a more timely and objective indicator than traditional subjective assessments.

Contribution

It proposes using PhD exchange networks as a new indicator for discipline reputation, addressing issues of reliability, comparability, and timeliness in evaluation methods.

Findings

PhD exchange networks effectively explain discipline reputation.

Horizontal and downward employment flows reveal structural characteristics.

Network evolution trends can warn of discipline quality changes.

Abstract

When reputation evaluation indicators become targets, existing indicators will lose the role of indicating the true quality; At present, the evaluation of discipline reputation mostly focuses on subjective evaluation based on objective data, and there is a dispute about reliability and validity; Due to different indicators and weight settings, it is difficult to make horizontal comparison among disciplines; The evaluation also has a certain time lag. In order to solve the above four problems, this study explores a new method of discipline reputation evaluation. Taking the business administration discipline as an example, it collects data of 5848 doctoral graduates who first entered teaching posts, establishes a directed adjacency matrix from the employment unit to the doctoral degree awarding unit, and uses the theory and method of social network analysis to conduct quantitative analysis on the doctoral mutual employment network. The results show that: (1) PhD exchange network can explain discipline reputation and is a new indicator to measure discipline reputation; (2) From the perspective of employment behavior among colleges and universities, there is horizontal flow and downward flow between the head colleges and universities, and downward flow is mainly among the middle and lower colleges. There is a time lag between college talent recruitment and academic achievement output. Therefore, the mining of the structural characteristics and network evolution trend of the PhD exchange network based on the "foot voting" of doctoral graduates is faster than the discipline ranking based on the follow-up achievement indicators to reflect the changes in the discipline quality, which can be used to warn the changes in the discipline quality.