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Topics in dynamic research communities: An exploratory study for the field of information retrieval
Journal article   Peer reviewed

Topics in dynamic research communities: An exploratory study for the field of information retrieval

Erjia Yan, Ying Ding, Staša Milojević and Cassidy R Sugimoto
Journal of informetrics, v 6(1), pp 140-153
2012
DOI: https://doi.org/10.1016/j.joi.2011.10.001

Abstract

Latent Dirichlet Allocation Knowledge discovery Coauthorship Community Network
► We examine how research topics are mixed and matched in evolving research communities. ► A hybrid approach integrating both topic identification and community detection techniques is proposed. ► Communities and topics are interwoven and co-evolving. ► Only 30% of the authors continuously published in IR. ► Biomedical and web application related topics are becoming more popular in recent time periods. Research topics and research communities are not disconnected from each other: communities and topics are interwoven and co-evolving. Yet, scientometric evaluations of topics and communities have been conducted independently and synchronically, with researchers often relying on homogeneous unit of analysis, such as authors, journals, institutions, or topics. Therefore, new methods are warranted that examine the dynamic relationship between topics and communities. This paper examines how research topics are mixed and matched in evolving research communities by using a hybrid approach which integrates both topic identification and community detection techniques. Using a data set on information retrieval (IR) publications, two layers of enriched information are constructed and contrasted: one is the communities detected through the topology of coauthorship network and the other is the topics of the communities detected through the topic model. We find evidence to support the assumption that IR communities and topics are interwoven and co-evolving, and topics can be used to understand the dynamics of community structures. We recommend the use of the hybrid approach to study the dynamic interactions of topics and communities.

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50 citations in Web of Science
57 citations in Scopus

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Web of Science research areas
Computer Science, Interdisciplinary Applications
Information Science & Library Science
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