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RESEARCH COLLABORATION OF ARTIFICIAL INTELLIGENCE LITERATURE OUTPUT: A SCIENTOMETRIC ANALYSIS

RESEARCH COLLABORATION OF ARTIFICIAL INTELLIGENCE LITERATURE OUTPUT: A SCIENTOMETRIC ANALYSIS. Presented by S.JEYAPRIYA, 2 nd MLIS, BDU, Trichy Guide Dr. N.AMSAVENI Assistant Professor, BDU, Trichy - 24. INTRODUCTION.

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RESEARCH COLLABORATION OF ARTIFICIAL INTELLIGENCE LITERATURE OUTPUT: A SCIENTOMETRIC ANALYSIS

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  1. RESEARCH COLLABORATION OF ARTIFICIAL INTELLIGENCE LITERATURE OUTPUT: A SCIENTOMETRIC ANALYSIS Presented by S.JEYAPRIYA, 2nd MLIS, BDU, Trichy Guide Dr. N.AMSAVENI Assistant Professor, BDU, Trichy - 24

  2. INTRODUCTION Scientometric studies are used to identify the pattern of publication, authorship, citations, growth pattern and other attributes and secondary journal coverage. In the present study, we did the Scientometric study of the research performance on Artificial Intelligence, a significantly growing area in the knowledge-driven world.

  3. Scientometrics Scientometrics, according to Garfield, is “the study of the measurement of scientific and technological progress (Garfield, 1979). Its origin is in the quantitative study of science policy research, or the science of science, which focuses on a wide variety of quantitative measurements, or indicators, of science at large. The 1970s saw the development of Scientometric as an operational activity - a response to the pressing demand for the ‘measuring of science’, especially in Russia and the USA. Since Vassily V. Nalimov coined the term ‘Scientometric’ in the 1960s.

  4. SCOPE OF THE PRESENT STUDY Different kinds of sources are published related the artificial intelligence research and its consequence on maintaining the information technology. The database (WoS) covers (Bibliographic data) information relating to the titles, authors, author affiliation, methodology adopted and the continent and country coverage of the comprehensive publications during the study period (1981 to 2010). It aims to evaluate the research activity of the Continent and Country wise output on Artificial Intelligence research.

  5. OBJECTIVES OF THE STUDY To identify year wise growth, RGR and exponential growth rate of artificial intelligence output. To analyse the authorship pattern, prolific authors and examine the extent of research Collaboration. To identify the citation scores and citation level and citation impact of the artificial intelligence research output. To apprehend and test of collaborative index, degrees of collaboration and h – index value; To find out the prolific authors performance, authorship pattern of research output on Artificial intelligence. To apply the Lotka’s law for measuring the n value for contributing authors To identify the weak and strong productivity of various continent and different countries.

  6. ANALYSIS AND INTERPRETATION This study is based on scientometric analysis of research trend of artificial intelligence literature output for the years 1981 - 2010. Scientometrics has typically been defined as the quantitative study of science and technology. Scientometrics includes all quantitative aspects of the science of science, communication in science and science policy (Wilson 2001).

  7. Figure 4.1: Year wise Growth Trends in AI output during 1981 to 2010

  8. Relative Growth Rate RGR values are the First decade 0.24; Second decade 0.15 and Third decade 0.84. and Doubling Time (Dt) value measured from this analysis is for First decade 3.18 years, Second decade value is 12.26 and Third year value is 13.7 yrs. Overall mean relative growth rate value is 0.16 Overall mean Doubling Time value is 9.71 years.

  9. CITATION IMPACT OF RESEARCH OUTPUT Impact suggested by Nagpaul (1995), Garg and Pandhi (1999) have been used for inter comparison of quality by making unit of citation indicators such as CPP and TNP % (Garg et al. 2009). CPP is based on the publication output and the number of citations received by these papers, citation per paper for different countries and different institutions has been calculated. Citation per paper has been calculated by using the following formula:

  10. CITATION ANALYSISTable 4.3: Distributions of Citation on artificial intelligence research • Out of the total Indian publications of Artificial intelligence is 10,795 papers, with an average output of 359.83 papers per year. • Total citation score value is 1,07,808, average citation per article is 9.986. • Analysis of citation data indicates that, out of the 10,795 published papers, 3920 (36.31 %) papers did not have any citations. Remaining (6875) 63.69 % of articles had one or more citations. • 4184 (38.75%) papers received citations between one to five. 1216 (11.26 %) papers received citations between six to ten. Remaining 1475 (13.66 %) of articles were received more than ten citations.

  11. Citation Scores and h – index of AI output Total TNP is 10795, and its average value of individual years is 359.83. Total citation Scores value is 107808 and its average value is 3593.6 Total Collaborative index value is 66.93, average CI value is 2.44. Total cited reference value is 298434 and its average value is 9947.8. Totally h index value is 765 and its average value is 25.5. 107808 TCS measured, and it calculated for individual year value is 3593.6 times. Total CPP value is 280 and its average value at individual year is 9.33.

  12. Cumulative Authorship pattern during 1981-2010 Single author contributed papers is 26.39 % double authors contributed papers is 21.41 % Triple authors contributing papers is 14.51% and Quadra authors contributing papers is 10.19 % respectively. It is found the collaborative author’s productivity is more than single author contribution. Single author productivity is only 26.39 percent whole multi author’s productivity is at 73.61 percents.

  13. Prolific Authors The authors of Klopman G, Rosenkranz HS, Emerenciano VD, HSU YY and Chau KW were identified the most productive authors. At specifically identified the Active Author is Chau KW.

  14. Degree of Collaboration • The degree of collaboration is 0.74 during the study period 1981 to 2010. i.e., out of the total 10795 literature published, 74 percentages of them are published under joint venture. • During the year 1981 to 2010 the degree of collaboration was of a constant value of 0.73 and 0.71. • It is seen clearly from the above that the degree of collaboration in producing research output on Artificial intelligence research has shown an increasing trend during the study period since it is a new discipline. • Based on this study, the result of the degree of collaboration C = 0.74. i.e, 74 percent of collaborative authors’ articles published during the study periods.

  15. Showing Lotka’s Law of Author Productivity It explains the fact that the tabulated value shows that observed authors’ value is higher than the expected value. Thus the present analysis clearly invalidates Lotka's findings.

  16. Continent Wise Research Output of Artificial intelligence European and North American continent has highest number of publications and the largest TCS. They dominated in the first and second position. Asian continent, Australia continent, South America and Africa continents were stood in the position of third, fourth, fifth and sixth with regards to the artificial intelligence research out put.

  17. Figure 4.3: Continent wise research output of Artificial intelligence

  18. FINDINGS Distribution by different sources of research output on Artificial intelligence publications when examined reveals a maximum contribution in the years of 2010, 2009 and 2006. The entire study period records a mean RGR of 0.16. The DT for publications at the cumulative level has been computed at 9.71 years. Analysis of citation data indicates that, out of the 10,795 published papers, 3920 (36.31 %) papers did not have any citation and the remaining 63.69 percents had one or more citations. It is seen from the authorship pattern analysis that collaborative author’s productivity is more than single author contribution. The author of “Klopman G” has published the highest number of articles have been 33 (0.13 %). At specifically identified the Active Author is Chau KW. The degree of collaboration is 0.74 during the study periods of 1981 to 2010. Continent wise analysis that the European continent has taken the first place. UK, USA, France and Spain are most productive countries.

  19. CONCLUSION Due to technological importance and expected economic activity, Artificial intelligence has been intensively investigated by scientometric methods. In this study, the current status of artificial intelligence has been presented. Initially frequency and percentile method have been evolved chronologically.

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