Data-driven Pattern Analysis of Acknowledgments in the Biomedical Domain

Juyoung An, Sieun Jeon, Teryn Jones, Min Song

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


Our motivation for conducting this research is driven by the lack of studies focusing on the acknowledgments sections of published papers. Another motivation is the lack of a study examining the countries and organizations mentioned in the acknowledgments section and their influence—something that cannot be analyzed using a citation or co-authorship relationship. Concentrating on the qualitative aspects of acknowledgments has been limited because of the atypical pattern of the acknowledgment section. Our research aims to identify useful information hidden within the acknowledgment sections of the articles stored in the PubMed Central database and to analyze a map of influence via a country-acknowledgment network. To solve the problems, we use the topic modeling to analyze topics of acknowledgments and conduct a basic network analysis to find the difference in the co-the country network and acknowledgment network. A word-embedding model is used to compare the semantic similarity that exists between the authors and countries extracted from our original dataset. The result of topic modeling suggests that funding has become a critical topic in acknowledgments. The results of network analysis indicate that some large countries work as hubs in terms of both implicitly and explicitly while revealing that some countries such as China do not frequently work with other countries. The word-embedding model built by acknowledgments suggests that the authors frequently referenced in acknowledgments are also likely to be referred to in a similar context. It also implies that the publishing country of a paper has little effect on whether it receives an acknowledgment from any other specific country. Through these results, we conclude that the content in acknowledgments extracted from the papers can be divided into two categories—funding and appreciation. We also find that there is no clear relationship between the publication country and the countries mentioned in the acknowledgment section.

Original languageEnglish
Pages (from-to)35-48
Number of pages14
JournalData and Information Management
Issue number1
Publication statusPublished - 2017 Sept 1

Bibliographical note

Funding Information:
Along with the empirical analysis of acknowledgment, Cronin & Weaver (1995) claimed that acknowledgments “define a variety of cognitive and social relationships between researchers and across discipline,” and set acknowledgment as a component of the “Reward Triangle,” which consists of authorship, citation, and acknowledgment. He emphasized that acknowledgment had not been utilized as much as the other components of the “Reward Triangle” notwithstanding its ability to map networks of influence. Meanwhile, in the late 1990s, most studies on acknowledgment placed stress on funding information mentioned in the acknowledgment section, which is helpful when analyzing its effects on funding. Lewison (1994) collected acknowledgments on funding from European Community’s Biotechnology Action Programme (BAP), which aimed to support high-quality research and to foster the construction of European scientific community. He evaluated the fulfillment of these two purposes by counting the number of citations and nations belonging to the papers that contain funding acknowledgments about BAP. In a similar way, Lewison (1998) compared the impact of papers funded by some organizations to those funded by no one. The result showed that the impact of papers that included acknowledgments on different organizations considerably varied, and the papers that did not include acknowledgments had less impact than those that contained acknowledgments. This tendency was supported by Lewison & Dawson (1998) who stated that “research supported by several funding bodies is likely to be of superior quality to that supported by only a single body or by none” in the biomedical domain (p.18).

Publisher Copyright:
© 2017 © 2017 Juyoung An et al.

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Library and Information Sciences


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