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Mining research trends with anomaly detection models: the case of social computing research

Author

Listed:
  • Qing Cheng

    (National University of Defense Technology)

  • Xin Lu

    (National University of Defense Technology
    Flowminder Foundation
    Karolinska Institutet
    Chinese Centre for Disease Control and Prevention)

  • Zhong Liu

    (National University of Defense Technology)

  • Jincai Huang

    (National University of Defense Technology)

Abstract

We proposed in this study to use anomaly detection models to discover research trends. The application was illustrated by applying a rule-based anomaly detector (WSARE), which was typically used for biosurveillance purpose, in the research trend analysis in social computing research. Based on articles collected from SCI-EXPANDED and CPCI-S databases during 2000 to 2013, we found that the number of social computing studies went up significantly in the past decade, with computer science and engineering among the top important subjects. Followed by China, USA was the largest contributor for studies in this field. According to anomaly detected by the WSARE, social computing research gradually shifted from its traditional fields such as computer science and engineering, to the fields of medical and health, and communication, etc. There was an emerging of various new subjects in recent years, including sentimental analysis, crowdsourcing and e-health. We applied an interdisciplinary network evolution analysis to track changes in interdisciplinary collaboration, and found that most subject categories closely collaborate with subjects of computer science and engineering. Our study revealed that, anomaly detection models had high potentials in mining hidden research trends and may provided useful tools in the study of forecasting in other fields.

Suggested Citation

  • Qing Cheng & Xin Lu & Zhong Liu & Jincai Huang, 2015. "Mining research trends with anomaly detection models: the case of social computing research," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(2), pages 453-469, May.
    • Handle: RePEc:spr:scient:v:103:y:2015:i:2:d:10.1007_s11192-015-1559-9
    DOI: 10.1007/s11192-015-1559-9
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    References listed on IDEAS

    as
    1. Iñaki Ucar & Felipe López-Fernandino & Pablo Rodriguez-Ulibarri & Laura Sesma-Sanchez & Veronica Urrea-Micó & Joaquín Sevilla, 2014. "Growth in the number of references in engineering journal papers during the 1972–2013 period," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1855-1864, March.
    2. Xianwen Wang & Zhi Wang & Shenmeng Xu, 2013. "Tracing scientist’s research trends realtimely," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(2), pages 717-729, May.
    3. Wolfgang Glänzel & Henk F. Moed, 2013. "Opinion paper: thoughts and facts on bibliometric indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(1), pages 381-394, July.
    4. B. S. Kademani & Anil Sagar & Ganesh Surwase & K. Bhanumurthy, 2013. "Publication trends in materials science: a global perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 1275-1295, March.
    5. Wolfgang Glänzel, 2013. "High-end performance or outlier? Evaluating the tail of scientometric distributions," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(1), pages 13-23, October.
    6. Limei Zhao & Qingpu Zhang, 2011. "Mapping knowledge domains of Chinese digital library research output, 1994–2010," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 51-87, October.
    7. Wolfgang Glänzel, 2000. "Science in Scandinavia: A Bibliometric Approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 48(2), pages 121-150, September.
    8. Gangan Prathap, 2014. "Single parameter indices and bibliometric outliers," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(3), pages 1781-1787, December.
    9. Xingjian Liu & F. Benjamin Zhan & Song Hong & Beibei Niu & Yaolin Liu, 2012. "A bibliometric study of earthquake research: 1900–2010," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(3), pages 747-765, September.
    10. Jun-Ying Fu & Xu Zhang & Yun-Hua Zhao & Dar-Zen Chen & Mu-Hsuan Huang, 2012. "Global performance of traditional Chinese medicine over three decades," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(3), pages 945-958, March.
    11. Yue Hu & Jun Sun & Weimin Li & Yunlong Pan, 2014. "A scientometric study of global electric vehicle research," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 1269-1282, February.
    12. Wolfgang Glänzel, 2000. "Science in Scandinavia: A Bibliometric Approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 49(2), pages 357-357, October.
    13. Yanhua Zhuang & Xingjian Liu & Thuminh Nguyen & Qingqing He & Song Hong, 2013. "Global remote sensing research trends during 1991–2010: a bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(1), pages 203-219, July.
    14. Xin Shuai & Alberto Pepe & Johan Bollen, 2012. "How the Scientific Community Reacts to Newly Submitted Preprints: Article Downloads, Twitter Mentions, and Citations," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-8, November.
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