IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v122y2020i1d10.1007_s11192-019-03288-5.html
   My bibliography  Save this article

Review on emerging research topics with key-route main path analysis

Author

Listed:
  • Shuo Xu

    (Beijing University of Technology)

  • Liyuan Hao

    (Beijing University of Technology)

  • Xin An

    (Beijing Forestry University)

  • Hongshen Pang

    (Library, Shenzhen University)

  • Ting Li

    (Chinese Academy of Sciences)

Abstract

The fast development of the emerging research topics field results in hundreds of theoretical and empirical publications. However, to our knowledge, there is no comprehensive and objective literature review on this field until now. To this end, a citation network consisting of 1607 papers between 1965 and early 2019 is explored to discover the knowledge diffusion trajectory of the emerging research topics field by the key-route main path analysis approach, armed with the traversal weight of search path link count. From the convergence–divergence patterns in the local and global main paths, the development of emerging research topics field can be divided into three different stages: the emergence, exploration and development stages. In the meanwhile, several research drifts can also be observed: (1) from citation-based approaches to machine learning based ones, (2) from the measurement to the identification, and (3) from the papers to the patents. Finally, the directions of future research are suggested.

Suggested Citation

  • Shuo Xu & Liyuan Hao & Xin An & Hongshen Pang & Ting Li, 2020. "Review on emerging research topics with key-route main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 607-624, January.
  • Handle: RePEc:spr:scient:v:122:y:2020:i:1:d:10.1007_s11192-019-03288-5
    DOI: 10.1007/s11192-019-03288-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-019-03288-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11192-019-03288-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Meen Chul Kim & Chaomei Chen, 2015. "A scientometric review of emerging trends and new developments in recommendation systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(1), pages 239-263, July.
    2. Lingfei Wu & Dashun Wang & James A. Evans, 2019. "Large teams develop and small teams disrupt science and technology," Nature, Nature, vol. 566(7744), pages 378-382, February.
    3. Luís M. A. Bettencourt & David I. Kaiser & Jasleen Kaur & Carlos Castillo-Chávez & David E. Wojick, 2008. "Population modeling of the emergence and development of scientific fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 75(3), pages 495-518, June.
    4. Kyebambe, Moses Ntanda & Cheng, Ge & Huang, Yunqing & He, Chunhui & Zhang, Zhenyu, 2017. "Forecasting emerging technologies: A supervised learning approach through patent analysis," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 236-244.
    5. Lee, Changyong & Kwon, Ohjin & Kim, Myeongjung & Kwon, Daeil, 2018. "Early identification of emerging technologies: A machine learning approach using multiple patent indicators," Technological Forecasting and Social Change, Elsevier, vol. 127(C), pages 291-303.
    6. Bart Verspagen, 2007. "Mapping Technological Trajectories As Patent Citation Networks: A Study On The History Of Fuel Cell Research," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 10(01), pages 93-115.
    7. Christian Weismayer & Ilona Pezenka, 2017. "Identifying emerging research fields: a longitudinal latent semantic keyword analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(3), pages 1757-1785, December.
    8. Bo Jarneving, 2005. "A comparison of two bibliometric methods for mapping of the research front," Scientometrics, Springer;Akadémiai Kiadó, vol. 65(2), pages 245-263, November.
    9. Ho, Jonathan C. & Saw, Ewe-Chai & Lu, Louis Y.Y. & Liu, John S., 2014. "Technological barriers and research trends in fuel cell technologies: A citation network analysis," Technological Forecasting and Social Change, Elsevier, vol. 82(C), pages 66-79.
    10. Sumita Raghuram & Philipp Tuertscher & Raghu Garud, 2010. "Research Note ---Mapping the Field of Virtual Work: A Cocitation Analysis," Information Systems Research, INFORMS, vol. 21(4), pages 983-999, December.
    11. Alba Santa Soriano & Carolina Lorenzo Álvarez & Rosa María Torres Valdés, 2018. "Bibliometric analysis to identify an emerging research area: Public Relations Intelligence—a challenge to strengthen technological observatories in the network society," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(3), pages 1591-1614, June.
    12. Vincent C. Ma & John S. Liu, 2016. "Exploring the research fronts and main paths of literature: a case study of shareholder activism research," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(1), pages 33-52, October.
    13. Kathleen Scalise & Diana J. Bernbaum & Mike Timms & S. Veeragoudar Harrell & Kristen Burmester & Cathleen A. Kennedy & Mark Wilson, 2007. "Adaptive technology for e‐learning: principles and case studies of an emerging field," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(14), pages 2295-2309, December.
    14. Hanning Guo & Scott Weingart & Katy Börner, 2011. "Mixed-indicators model for identifying emerging research areas," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 421-435, October.
    15. Chaomei Chen & Fidelia Ibekwe‐SanJuan & Jianhua Hou, 2010. "The structure and dynamics of cocitation clusters: A multiple‐perspective cocitation analysis," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(7), pages 1386-1409, July.
    16. Olle Persson, 1994. "The intellectual base and research fronts of JASIS 1986–1990," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 45(1), pages 31-38, January.
    17. Small, Henry & Boyack, Kevin W. & Klavans, Richard, 2014. "Identifying emerging topics in science and technology," Research Policy, Elsevier, vol. 43(8), pages 1450-1467.
    18. Rotolo, Daniele & Hicks, Diana & Martin, Ben R., 2015. "What is an emerging technology?," Research Policy, Elsevier, vol. 44(10), pages 1827-1843.
    19. Kevin W. Boyack & Richard Klavans, 2010. "Co‐citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    20. Zhu, Hengmin & Yin, Xicheng & Ma, Jing & Hu, Wei, 2016. "Identifying the main paths of information diffusion in online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 320-328.
    21. Chaomei Chen, 2006. "CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(3), pages 359-377, February.
    22. Dangzhi Zhao & Andreas Strotmann, 2014. "The knowledge base and research front of information science 2006–2010: An author cocitation and bibliographic coupling analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(5), pages 995-1006, May.
    23. Chaomei Chen & Fidelia Ibekwe-SanJuan & Jianhua Hou, 2010. "The structure and dynamics of cocitation clusters: A multiple-perspective cocitation analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(7), pages 1386-1409, July.
    24. Liu, Xiang & Jiang, Tingting & Ma, Feicheng, 2013. "Collective dynamics in knowledge networks: Emerging trends analysis," Journal of Informetrics, Elsevier, vol. 7(2), pages 425-438.
    25. Ivana Roche & Dominique Besagni & Claire François & Marianne Hörlesberger & Edgar Schiebel, 2010. "Identification and characterisation of technological topics in the field of Molecular Biology," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(3), pages 663-676, March.
    26. Richard Klavans & Kevin W. Boyack, 2011. "Using global mapping to create more accurate document‐level maps of research fields," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(1), pages 1-18, January.
    27. Serhat Burmaoglu & Olivier Sartenaer & Alan Porter & Munan Li, 2019. "Analysing the theoretical roots of technology emergence: an evolutionary perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 97-118, April.
    28. Ivan Jarić & Jelena Knežević-Jarić & Mirjana Lenhardt, 2014. "Relative age of references as a tool to identify emerging research fields with an application to the field of ecology and environmental sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(2), pages 519-529, August.
    29. Richard Klavans & Kevin W. Boyack, 2011. "Using global mapping to create more accurate document-level maps of research fields," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(1), pages 1-18, January.
    30. Mor Naaman & Hila Becker & Luis Gravano, 2011. "Hip and trendy: Characterizing emerging trends on Twitter," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(5), pages 902-918, May.
    31. Kevin W. Boyack & Richard Klavans, 2014. "Creation of a highly detailed, dynamic, global model and map of science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(4), pages 670-685, April.
    32. Henry Small, 1973. "Co‐citation in the scientific literature: A new measure of the relationship between two documents," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 24(4), pages 265-269, July.
    33. Vladimir Batagelj & Anuška Ferligoj & Flaminio Squazzoni, 2017. "The emergence of a field: a network analysis of research on peer review," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 503-532, October.
    34. Naoki Shibata & Yuya Kajikawa & Yoshiyuki Takeda & Katsumori Matsushima, 2009. "Comparative study on methods of detecting research fronts using different types of citation," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(3), pages 571-580, March.
    35. Joung, Junegak & Kim, Kwangsoo, 2017. "Monitoring emerging technologies for technology planning using technical keyword based analysis from patent data," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 281-292.
    36. Xu, Shuo & Hao, Liyuan & An, Xin & Yang, Guancan & Wang, Feifei, 2019. "Emerging research topics detection with multiple machine learning models," Journal of Informetrics, Elsevier, vol. 13(4).
    37. Lutz Bornmann & Alexander Tekles, 2019. "Disruptive papers published in Scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 331-336, July.
    38. Yu Liu & Dan Lin & Xiujuan Xu & Shimin Shan & Quan Z. Sheng, 2018. "Multi-views on Nature Index of Chinese academic institutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 823-837, March.
    39. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min & Lin, Bruce J.Y., 2013. "Data envelopment analysis 1978–2010: A citation-based literature survey," Omega, Elsevier, vol. 41(1), pages 3-15.
    40. Kevin W. Boyack & Richard Klavans, 2010. "Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    41. Dangzhi Zhao & Andreas Strotmann, 2008. "Evolution of research activities and intellectual influences in information science 1996–2005: Introducing author bibliographic‐coupling analysis," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(13), pages 2070-2086, November.
    42. S. Phineas Upham & Henry Small, 2010. "Emerging research fronts in science and technology: patterns of new knowledge development," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(1), pages 15-38, April.
    43. Woondong Yeo & Seonho Kim & Jae-Min Lee & Jaewoo Kang, 2014. "Aggregative and stochastic model of main path identification: a case study on graphene," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 633-655, January.
    44. Steven A. Morris & G. Yen & Zheng Wu & Benyam Asnake, 2003. "Time line visualization of research fronts," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 54(5), pages 413-422, March.
    45. John S. Liu & Louis Y.Y. Lu, 2012. "An integrated approach for main path analysis: Development of the Hirsch index as an example," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(3), pages 528-542, March.
    46. Woo Hyoung Lee, 2008. "How to identify emerging research fields using scientometrics: An example in the field of Information Security," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(3), pages 503-525, September.
    47. Ping Xie, 2015. "Study of international anticancer research trends via co-word and document co-citation visualization analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(1), pages 611-622, October.
    48. Jarneving, Bo, 2007. "Bibliographic coupling and its application to research-front and other core documents," Journal of Informetrics, Elsevier, vol. 1(4), pages 287-307.
    49. Bhupatiraju, Samyukta & Nomaler, Önder & Triulzi, Giorgio & Verspagen, Bart, 2012. "Knowledge flows – Analyzing the core literature of innovation, entrepreneurship and science and technology studies," Research Policy, Elsevier, vol. 41(7), pages 1205-1218.
    50. Mor Naaman & Hila Becker & Luis Gravano, 2011. "Hip and trendy: Characterizing emerging trends on Twitter," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(5), pages 902-918, May.
    51. John S. Liu & Louis Y.Y. Lu, 2012. "An integrated approach for main path analysis: Development of the Hirsch index as an example," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(3), pages 528-542, March.
    52. John S. Liu & Louis Y. Y. Lu & Mei Hsiu-Ching Ho, 2019. "A few notes on main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 379-391, April.
    53. Chengliang Liu & Qinchang Gui, 2016. "Mapping intellectual structures and dynamics of transport geography research: a scientometric overview from 1982 to 2014," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(1), pages 159-184, October.
    54. Qi Wang, 2018. "A bibliometric model for identifying emerging research topics," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(2), pages 290-304, February.
    55. Russell J. Funk & Jason Owen-Smith, 2017. "A Dynamic Network Measure of Technological Change," Management Science, INFORMS, vol. 63(3), pages 791-817, March.
    56. Show-Ling Jang & Yun-Chen Yu & Tzu-Ya Wang, 2011. "Emerging firms in an emerging field: an analysis of patent citations in electronic-paper display technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 259-272, October.
    57. Mogoutov, Andrei & Kahane, Bernard, 2007. "Data search strategy for science and technology emergence: A scalable and evolutionary query for nanotechnology tracking," Research Policy, Elsevier, vol. 36(6), pages 893-903, July.
    58. Wolfgang Glänzel & Bart Thijs, 2012. "Using ‘core documents’ for detecting and labelling new emerging topics," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(2), pages 399-416, May.
    59. Yoshiyuki Takeda & Yuya Kajikawa, 2009. "Optics: a bibliometric approach to detect emerging research domains and intellectual bases," Scientometrics, Springer;Akadémiai Kiadó, vol. 78(3), pages 543-558, March.
    60. Aleks Aris & Ben Shneiderman & Vahed Qazvinian & Dragomir Radev, 2009. "Visual overviews for discovering key papers and influences across research fronts," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(11), pages 2219-2228, November.
    61. Kuhlmann, Stefan & Stegmaier, Peter & Konrad, Kornelia, 2019. "The tentative governance of emerging science and technology—A conceptual introduction," Research Policy, Elsevier, vol. 48(5), pages 1091-1097.
    62. Stephen F. Carley & Nils C. Newman & Alan L. Porter & Jon G. Garner, 2018. "An indicator of technical emergence," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 35-49, April.
    63. Ryosuke L. Ohniwa & Aiko Hibino & Kunio Takeyasu, 2010. "Trends in research foci in life science fields over the last 30 years monitored by emerging topics," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(1), pages 111-127, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lu, Kun & Yang, Guancan & Wang, Xue, 2022. "Topics emerged in the biomedical field and their characteristics," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    2. Dejian Yu & Zhaoping Yan, 2021. "Knowledge diffusion of supply chain bullwhip effect: main path analysis and science mapping analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8491-8515, October.
    3. Huang, Lu & Chen, Xiang & Ni, Xingxing & Liu, Jiarun & Cao, Xiaoli & Wang, Changtian, 2021. "Tracking the dynamics of co-word networks for emerging topic identification," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    4. Lai, Kuei-Kuei & Bhatt, Priyanka C. & Kumar, Vimal & Chen, Hsueh-Chen & Chang, Yu-Hsin & Su, Fang-Pei, 2021. "Identifying the impact of patent family on the patent trajectory: A case of thin film solar cells technological trajectories," Journal of Informetrics, Elsevier, vol. 15(2).
    5. Yu, Dejian & Pan, Tianxing, 2021. "Tracing the main path of interdisciplinary research considering citation preference: A case from blockchain domain," Journal of Informetrics, Elsevier, vol. 15(2).
    6. Aliakbar Pourhatami & Mohammad Kaviyani-Charati & Bahareh Kargar & Hamed Baziyad & Maryam Kargar & Carlos Olmeda-Gómez, 2021. "Mapping the intellectual structure of the coronavirus field (2000–2020): a co-word analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6625-6657, August.
    7. Wenjie Wei & Hongxu Liu & Zhuanlan Sun, 2022. "Cover papers of top journals are reliable source for emerging topics detection: a machine learning based prediction framework," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4315-4333, August.
    8. Chen, Liang & Xu, Shuo & Zhu, Lijun & Zhang, Jing & Xu, Haiyun & Yang, Guancan, 2022. "A semantic main path analysis method to identify multiple developmental trajectories," Journal of Informetrics, Elsevier, vol. 16(2).
    9. Concepta McManus & Abilio Afonso Baeta Neves & Alvaro Toubes Prata, 2021. "Scientific publications from non-academic sectors and their impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(11), pages 8887-8911, November.
    10. Zhenyu Yang & Wenyu Zhang & Zhimin Wang & Xiaoling Huang, 2024. "A deep learning-based method for predicting the emerging degree of research topics using emerging index," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(7), pages 4021-4042, July.
    11. Mike Thelwall & Pardeep Sud, 2021. "Do new research issues attract more citations? A comparison between 25 Scopus subject categories," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(3), pages 269-279, March.
    12. Abderahman Rejeb & Alireza Abdollahi & Karim Rejeb & Mohamed M. Mostafa, 2023. "Tracing knowledge evolution flows in scholarly restaurant research: a main path analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2183-2209, June.
    13. Yu, Dejian & Sheng, Libo, 2021. "Influence difference main path analysis: Evidence from DNA and blockchain domain citation networks," Journal of Informetrics, Elsevier, vol. 15(4).
    14. Xu, Shuo & Hao, Liyuan & Yang, Guancan & Lu, Kun & An, Xin, 2021. "A topic models based framework for detecting and forecasting emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    15. Katchanov, Yurij L. & Markova, Yulia V., 2022. "Dynamics of senses of new physics discourse: Co-keywords analysis," Journal of Informetrics, Elsevier, vol. 16(1).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xu, Shuo & Hao, Liyuan & Yang, Guancan & Lu, Kun & An, Xin, 2021. "A topic models based framework for detecting and forecasting emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    2. Xu, Haiyun & Winnink, Jos & Yue, Zenghui & Zhang, Huiling & Pang, Hongshen, 2021. "Multidimensional Scientometric indicators for the detection of emerging research topics," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    3. Xu, Shuo & Hao, Liyuan & An, Xin & Yang, Guancan & Wang, Feifei, 2019. "Emerging research topics detection with multiple machine learning models," Journal of Informetrics, Elsevier, vol. 13(4).
    4. Lu, Kun & Yang, Guancan & Wang, Xue, 2022. "Topics emerged in the biomedical field and their characteristics," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    5. Pin Li & Guoli Yang & Chuanqi Wang, 2019. "Visual topical analysis of library and information science," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1753-1791, December.
    6. Kwon, Seokbeom & Liu, Xiaoyu & Porter, Alan L. & Youtie, Jan, 2019. "Research addressing emerging technological ideas has greater scientific impact," Research Policy, Elsevier, vol. 48(9), pages 1-1.
    7. Rotolo, Daniele & Hicks, Diana & Martin, Ben R., 2015. "What is an emerging technology?," Research Policy, Elsevier, vol. 44(10), pages 1827-1843.
    8. Carlos Olmeda-Gómez & Carlos Romá-Mateo & Maria-Antonia Ovalle-Perandones, 2019. "Overview of trends in global epigenetic research (2009–2017)," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1545-1574, June.
    9. Xuefeng Wang & Shuo Zhang & Yuqin liu, 2022. "ITGInsight–discovering and visualizing research fronts in the scientific literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6509-6531, November.
    10. Yang, Siluo & Han, Ruizhen & Wolfram, Dietmar & Zhao, Yuehua, 2016. "Visualizing the intellectual structure of information science (2006–2015): Introducing author keyword coupling analysis," Journal of Informetrics, Elsevier, vol. 10(1), pages 132-150.
    11. Chen, Kaihua & Zhang, Yi & Fu, Xiaolan, 2019. "International research collaboration: An emerging domain of innovation studies?," Research Policy, Elsevier, vol. 48(1), pages 149-168.
    12. Wooseok Jang & Yongtae Park & Hyeonju Seol, 2021. "Identifying emerging technologies using expert opinions on the future: A topic modeling and fuzzy clustering approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6505-6532, August.
    13. Porter, Alan L. & Chiavetta, Denise & Newman, Nils C., 2020. "Measuring tech emergence: A contest," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    14. Small, Henry & Boyack, Kevin W. & Klavans, Richard, 2014. "Identifying emerging topics in science and technology," Research Policy, Elsevier, vol. 43(8), pages 1450-1467.
    15. Serhat Burmaoglu & Olivier Sartenaer & Alan Porter & Munan Li, 2019. "Analysing the theoretical roots of technology emergence: an evolutionary perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 97-118, April.
    16. Mauricio Marrone, 2020. "Application of entity linking to identify research fronts and trends," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 357-379, January.
    17. Chaker Jebari & Enrique Herrera-Viedma & Manuel Jesus Cobo, 2021. "The use of citation context to detect the evolution of research topics: a large-scale analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 2971-2989, April.
    18. Mu-hsuan Huang & Chia-Pin Chang, 2015. "A comparative study on detecting research fronts in the organic light-emitting diode (OLED) field using bibliographic coupling and co-citation," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2041-2057, March.
    19. Yang, Siluo & Wang, Feifei, 2015. "Visualizing information science: Author direct citation analysis in China and around the world," Journal of Informetrics, Elsevier, vol. 9(1), pages 208-225.
    20. Sjögårde, Peter & Ahlgren, Per, 2018. "Granularity of algorithmically constructed publication-level classifications of research publications: Identification of topics," Journal of Informetrics, Elsevier, vol. 12(1), pages 133-152.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:122:y:2020:i:1:d:10.1007_s11192-019-03288-5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.