An exploration to visualise the emerging trends of technology foresight based on an improved technique of co-word analysis and relevant literature data of WOS

ABSTRACT To explore the possible research fronts and emerging trends of technology foresight, through integrating co-occurrence of keywords and burst terms detection into an improved technique of co-word analysis based on the relevant literature in Web of Science is proposed. Based on the new analytical technique, the links among hot keywords, burst terms are probed, and the core literature related to the emerging trend or interdisciplinary researches are identified. Obviously, the attempts of new bibliometric method in this paper could be a valuable supplement to the traditional co-word analysis; meanwhile, it maybe is much more helpful for those interdisciplinary researchers.

[1]  M. Tahar Kechadi,et al.  Performance study of distributed Apriori-like frequent itemsets mining , 2010, Knowledge and Information Systems.

[2]  Pei-Chun Lee,et al.  Mapping knowledge structure by keyword co-occurrence: a first look at journal papers in Technology Foresight , 2010, Scientometrics.

[3]  Norberto F. Ezquerra,et al.  Constraining and summarizing association rules in medical data , 2006, Knowledge and Information Systems.

[4]  Meen Chul Kim,et al.  Emerging trends and new developments in regenerative medicine: a scientometric update (2000 – 2014) , 2014, Expert opinion on biological therapy.

[5]  Svetha Venkatesh,et al.  Event extraction using behaviors of sentiment signals and burst structure in social media , 2013, Knowledge and Information Systems.

[6]  H. Small,et al.  Identifying emerging topics in science and technology , 2014 .

[7]  Sujit Bhattacharya,et al.  Mapping a research area at the micro level using co-word analysis , 1998, Scientometrics.

[8]  Thomas J. Healy,et al.  An evolutionary approach , 1993 .

[9]  Gobinda G. Chowdhury,et al.  Bibliometric cartography of information retrieval research by using co-word analysis , 2001, Inf. Process. Manag..

[10]  Woo Hyoung Lee,et al.  How to identify emerging research fields using scientometrics: An example in the field of Information Security , 2008, Scientometrics.

[11]  P. Rousseeuw.  Silhouettes: a graphical aid to the interpretation and validation of cluster analysis , 1987 .

[12]  Alexander Sokolov,et al.  Quantitative and qualitative approaches in Future-oriented Technology Analysis (FTA): From combination to integration? , 2013 .

[13]  Weiguang Wang,et al.  Visualization and quantitative study in bibliographic databases: A case in the field of university-industry cooperation , 2015, J. Informetrics.

[14]  Ivan Zupic,et al.  Bibliometric Methods in Management and Organization , 2014 .

[15]  M E J Newman,et al.  Modularity and community structure in networks. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[16]  Wen-Yang Lin,et al.  Automated support specification for efficient mining of interesting association rules , 2006, J. Inf. Sci..

[17]  Paul D. McNicholas,et al.  Standardising the lift of an association rule , 2008, Comput. Stat. Data Anal..

[18]  Ata Kabán,et al.  A dynamic bibliometric model for identifying online communities , 2007, Data Mining and Knowledge Discovery.

[19]  Chaomei Chen,et al.  A scientometric review of emerging trends and new developments in recommendation systems , 2015, Scientometrics.

[20]  Reinhard German,et al.  Technology foresight for medical device development through hybrid simulation: The ProHTA Project , 2015 .

[21]  Ryota Tomioka,et al.  Discovering Emerging Topics in Social Streams via Link-Anomaly Detection , 2014, IEEE Transactions on Knowledge and Data Engineering.

[22]  Katy Börner,et al.  Mixed-indicators model for identifying emerging research areas , 2011, Scientometrics.

[23]  Munan Li,et al.  A novel three-dimension perspective to explore technology evolution , 2015, Scientometrics.

[24]  K. Cuhls.  From forecasting to foresight processes—new participative foresight activities in Germany , 2003 .

[25]  Harold A. Linstone,et al.  Three eras of technology foresight , 2011 .

[26]  Tzung-Pei Hong,et al.  A novel method for constrained class association rule mining , 2015, Inf. Sci..

[27]  Qingqiang Wu,et al.  Co-word analysis of the trends in stem cells field based on subject heading weighting , 2011, Scientometrics.

[28]  Takashi Washio,et al.  An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data , 2000, PKDD.

[29]  Heiko A. von der Gracht,et al.  The influence of information and communication technology (ICT) on future foresight processes — Results from a Delphi survey , 2014 .

[30]  Guido Reger,et al.  Technology Foresight in Companies: From an Indicator to a Network and Process Perspective , 2001, Technol. Anal. Strateg. Manag..

[31]  Alan L. Porter,et al.  Tech mining: Text mining and visualization tools, as applied to nanoenhanced solar cells , 2011, WIREs Data Mining Knowl. Discov..

[32]  S. Breiner,et al.  Foresight in Science and Technology , 1996 .

[33]  Ben R. Martin,et al.  The origins of the concept of ‘foresight’ in science and technology: An insider's perspective , 2010 .

[34]  Francisco Herrera,et al.  Science mapping software tools: Review, analysis, and cooperative study among tools , 2011, J. Assoc. Inf. Sci. Technol..

[35]  Birgit Stelzer,et al.  Combining the scenario technique with bibliometrics for technology foresight: The case of personalized medicine , 2015 .

[36]  Jiancheng Guan,et al.  A bibliometric investigation of research performance in emerging nanobiopharmaceuticals , 2011, J. Informetrics.

[37]  I. Miles.  The development of technology foresight: A review , 2010 .

[38]  Alan L. Porter,et al.  QTIP: Quick technology intelligence processes , 2005 .

[39]  Harold A. Linstone,et al.  Technological forecasting and social change , 2011 .

[40]  Alan L. Porter,et al.  Tech mining to generate indicators of future national technological competitiveness: Nano-Enhanced Drug Delivery (NEDD) in the US and China , 2015 .

[41]  Chih-Young Hung,et al.  Strategic foresight using a modified Delphi with end-user participation: A case study of the iPad's impact on Taiwan's PC ecosystem , 2013 .

[42]  Loet Leydesdorff,et al.  Why Words and Co-Words Cannot Map the Development of the Sciences , 1997, J. Am. Soc. Inf. Sci..

[43]  Bernadette Foerster,et al.  Technology foresight for sustainable production in the German automotive supplier industry , 2015 .

[44]  Juan Julián Merelo Guervós,et al.  Automatic detection of trends in time-stamped sequences: an evolutionary approach , 2009, Soft Comput..

[45]  Chaomei Chen,et al.  CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature , 2006, J. Assoc. Inf. Sci. Technol..

[46]  Tomasz Imielinski,et al.  Mining association rules between sets of items in large databases , 1993, SIGMOD Conference.

[47]  Hsinchun Chen,et al.  Burst Detection From Multiple Data Streams: A Network-Based Approach , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[48]  Jon M. Kleinberg,et al.  Bursty and Hierarchical Structure in Streams , 2002, Data Mining and Knowledge Discovery.

[49]  Ronald N. Kostoff,et al.  Science and technology roadmaps , 2001, IEEE Trans. Engineering Management.

[50]  Nicolas Pasquier,et al.  Efficient Mining of Association Rules Using Closed Itemset Lattices , 1999, Inf. Syst..

[51]  E. Silerova,et al.  Knowledge and information systems , 2018 .

[52]  Tugrul U. Daim,et al.  Exploring the impact of technology foresight studies on innovation: Case of BRIC countries , 2012 .