A century of discovery: Mining 100 years of honey bee research

Abstract

Honey bees have been an important area of research and study going back at least to the days of Aristotle in the third century B.C. The amount and breadth of this research have been steadily increasing over time, especially during the modern age with the growing importance of honey bees to our society in agriculture, economics, food, medicine, and even computing technology. Even for those familiar with bees and scientific literature, the volume and diversity of information can be daunting. The aim of this study is to survey the last 100 years of available scientific research related to or inspired by honey bees and show its evolution, progression, and diversification through time by using text mining to conduct both a historical and topical analysis on the last 100 years of this research. This process shows how this research has grown and evolved over time while informing researchers of the depth, breadth, and dynamic nature of the research. This paper presents the analysis of the titles and abstracts of the 30,355 unique peer reviewed journal articles we identified related to honey bees and beekeeping and articulates relevant topics and changes over 100 years of bee research analyzed in ten time periods from 1917 through 2016. This study shows how honey bee research has evolved from a sub-field of other disciplines to a strong discipline in its own right and how it has further been enriched by contributions from other sciences.

Keywords:

• historical analysis
• content analysis
• data mining
• text mining
• honey bee research
• library and information science

Acknowledgments

We are grateful to our student work Preston MacDonald for his help in revising, synthesizing and formatting this work and to Project Apis m. for supporting some of this work with a Healthy Hives 2020 grant.

Disclosure statement

In accordance with Taylor & Francis policy and our ethical obligation as a researcher, I am reporting that authors James Wilkes and Joseph Cazier are shareholders in HiveTracks.com, a software and analytics firm focused on bee data, that may be affected by the research reported in the enclosed paper. I have disclosed those interests fully to Taylor & Francis, and I have in place an approved plan for managing any potential conflicts arising from that involvement. Additionally, this project was partially funded from a grant by Project Apis m.