An author topic analysis of tobacco regulation investigators

Ding Cheng Li, Janet Okamoto, Scott Leischow, Hongfang Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

To facilitate the implementation of the Family Smoking Prevention and Tobacco Control Act of 2009, the Federal Drug Agency (FDA) Center for Tobacco Products (CTP) has identified research priorities under the umbrella of tobacco regulatory science (TRS). As a newly introduced field, the current landscape of TRS research is unclear. In this work, we conducted a bibliometric study of TRS research by applying author topic modeling on MEDLINE citations published by currently-funded TRS principle investigators. Our initial results show that author topic modeling can address the issue of research interests reasonably. Furthermore, a network involving authors, topics and words can be established for more detailed bibliometric analysis. This network may also be useful to grantees and funding administrators in suggesting potential collaborators or identifying those that share common research interests for data harmonization or other purposes.

Original languageEnglish (US)
Title of host publicationTrends and Applications in Knowledge Discovery and Data Mining - PAKDD 2014 International Workshops
Subtitle of host publicationDANTH, BDM, MobiSocial, BigEC, CloudSD, MSMV-MBI, SDA, DMDA-Health, ALSIP, SocNet, DMBIH, BigPMA, Revised Selected Papers
EditorsWen-Chih Peng, Haixun Wang, Zhi-Hua Zhou, Tu Bao Ho, Vincent S. Tseng, Arbee L.P. Chen, James Bailey
PublisherSpringer Verlag
Pages616-627
Number of pages12
ISBN (Electronic)9783319131856
DOIs
StatePublished - Jan 1 2014
Externally publishedYes
EventInternational Workshops on Data Mining and Decision Analytics for Public Health, Biologically Inspired Data Mining Techniques, Mobile Data Management, Mining, and Computing on Social Networks, Big Data Science and Engineering on E-Commerce, Cloud Service Discovery, MSMV-MBI, Scalable Dats Analytics, Data Mining and Decision Analytics for Public Health and Wellness, Algorithms for Large-Scale Information Processing in Knowledge Discovery, Data Mining in Social Networks, Data Mining in Biomedical informatics and Healthcare, Pattern Mining and Application of Big Data in conjunction with 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2014 - Tainan, Taiwan, Province of China
Duration: May 13 2014May 16 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8643
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherInternational Workshops on Data Mining and Decision Analytics for Public Health, Biologically Inspired Data Mining Techniques, Mobile Data Management, Mining, and Computing on Social Networks, Big Data Science and Engineering on E-Commerce, Cloud Service Discovery, MSMV-MBI, Scalable Dats Analytics, Data Mining and Decision Analytics for Public Health and Wellness, Algorithms for Large-Scale Information Processing in Knowledge Discovery, Data Mining in Social Networks, Data Mining in Biomedical informatics and Healthcare, Pattern Mining and Application of Big Data in conjunction with 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2014
CountryTaiwan, Province of China
CityTainan
Period5/13/145/16/14

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Li, D. C., Okamoto, J., Leischow, S., & Liu, H. (2014). An author topic analysis of tobacco regulation investigators. In W-C. Peng, H. Wang, Z-H. Zhou, T. B. Ho, V. S. Tseng, A. L. P. Chen, & J. Bailey (Eds.), Trends and Applications in Knowledge Discovery and Data Mining - PAKDD 2014 International Workshops: DANTH, BDM, MobiSocial, BigEC, CloudSD, MSMV-MBI, SDA, DMDA-Health, ALSIP, SocNet, DMBIH, BigPMA, Revised Selected Papers (pp. 616-627). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8643). Springer Verlag. https://doi.org/10.1007/978-3-319-13186-3_55