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An overview of modeling and simulation using content analysis

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Abstract

Over the past six decades, Modeling and Simulation (M&S) has been used as a method or tool in many disciplines. While there is no doubt that the emergence of modern M&S is highly connected with that of Computing and Systems science, there is no clear evidence of the contribution of M&S to those disciplines. Further, while there is a growing body of knowledge (BoK) in M&S, there is no easy way to identify it due to the multidisciplinary nature of M&S. In this paper, we examine whether M&S is its own discipline by performing content analysis of a BoK in Computer Science. Content analysis is a research methodology that aims to identify key concepts and relationships in a body of text through computational means. It can be applied to research articles in a BoK to identify the prominent topics and themes. It can also be used to explore the evolution of a BoK over time or to identify the contribution of one BoK to another. The contribution of this paper is twofold; (1) the establishment of M&S as its own discipline and the examination of its relationship with the sister disciplines of Computer Science and Systems Engineering over the last 60 years and (2) the examination of the contribution of M&S to the sciences as represented in the Public Library of Science.

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Notes

  1. http://www.acm.org/about/class/ccs98-html.

  2. http://sag.sagepub.com/.

References

  • Ahuvia, A. (2001). Traditional, interpretive, and reception based content analyses: Improving the ability of content analysis to address issues of pragmatic and theoretical concern. Social Indicators Research, 54(2), 139–172.

    Article  Google Scholar 

  • Araten, M., Hixson, H. M., Hoggatt, A. C., Kiviat, P. J., Morris, M. F., Ockene, A., Reitman, J., Sussman J. M., & Wilson, J. R. (1992). The winter simulation conference: Perspectives of the founding fathers. In Proceedings of the 24th conference on Winter simulation (pp. 37–62). New York, NY: Association for Computing Machinery.

  • Banks, C. (2006). Academic night: Spring SIW 2006. In Proceedings of the 2006 Spring Simulation Interoperability Workshop (SIW) (pp. 1–3). Huntsville, AL: Society for Modeling and Simulation.

  • Banks, C. M., & McGinnis, M. L. (2008). Compelling challenges and recommended solutions: Developing a continuity of M&S education from public school to graduate studies. In Proceedings of the 2008 Spring simulation multiconference (pp. 773–780). San Diego, CA: Society for Computer Simulation International.

  • Berelson, B. (1952). Content analysis in communication research. Glencoe, IL: The Free Press.

    Google Scholar 

  • Chang, Y. H., Chang, C. Y., & Tseng, Y. H. (2010). Trends of science education research: An automatic content analysis. Journal of Science Education and Technology, 19(4), 315–331.

    Article  Google Scholar 

  • Cretchley, J., Rooney, D., & Gallois, C. (2010). Mapping a 40-year history with Leximancer: Themes and concepts in the Journal of Cross-Cultural Psychology. Journal of Cross-Cultural Psychology, 41(3), 318–328.

    Article  Google Scholar 

  • Crofts, K., & Bisman, J. (2010). Interrogating accountability: An illustration of the use of Leximancer software for qualitative data analysis. Qualitative Research in Accounting & Management, 7(2), 180–207.

    Article  Google Scholar 

  • Crookall, D. (2010). Serious games, debriefing, and simulation/gaming as a discipline. Simulation & Gaming, 41(6), 898–920.

    Article  Google Scholar 

  • Denning, P. J. (2005). Is computer science science? Communications of the ACM, 48(4), 27–31.

    Article  MathSciNet  Google Scholar 

  • Fishwick, P. (2014) Computing as model-based empirical science. In Proceedings of the 2nd ACM SIGSIM/PADS conference on principles of advanced discrete simulation (pp. 205–212). New York, NY: ACM.

  • Gasiorek, J., Giles, H., Holtgraves, T., & Robbins, S. (2012). Celebrating thirty years of the JLSP analyses and prospects. Journal of Language and Social Psychology, 31(4), 361–375.

    Article  Google Scholar 

  • Grimbeek, P., Bryer, F., Davies, M., & Bartlett, B. (2005). Themes and patterns in 3 years of abstracts from the international conference on cognition, language, and special education research: Identified by Leximancer analysis. Stimulating the ‘‘action’’ as participants in participatory research Brisbane. Australia: Griffith University, School of Cognition, Language, and Special Education, pp. 101–113.

  • Hollocks, B. W. (2006). Forty years of discrete-event simulation—a personal reflection. Journal of the Operational Research Society, 57(12), 1383–1399.

    Article  MATH  Google Scholar 

  • Hsieh, H. F., & Shannon, S. E. (2005). Three approaches to qualitative content analysis. Qualitative Health Research, 15(9), 1277–1288.

    Article  Google Scholar 

  • Jeon, W., Franke, G. R., Huhmann, B. A., & Phelps, J. (1999). Appeals in Korean magazine advertising: a content analysis and cross-cultural comparison. Asia Pacific Journal of Management, 16(2), 249–258.

    Article  Google Scholar 

  • Kassarjian, H. H. (1977). Content analysis in consumer research. Journal of Consumer Research, 4(1), 8–18.

    Article  Google Scholar 

  • Katsaliaki, K., & Mustafee, N. (2011). Applications of simulation within the healthcare context. Journal of the Operational Research Society, 62(8), 1431–1451.

    Article  Google Scholar 

  • Katsaliaki, K., Mustafee, N., Dwivedi, Y. K., Williams, T., & Wilson, J. M. (2010). A profile of OR Research and Practice published in the Journal of the Operational Research Society. Journal of the Operational Research Society, 61(1), 82–94.

    Article  MATH  Google Scholar 

  • Leximancer (2011). Leximancer Manual: Version 4. Resource document. https://www.leximancer.com/site-media/lm/science/Leximancer_Manual_Version_4_0.pdf. Accessed 28 Aug 2014.

  • Liesch, P. W., Håkanson, L., McGaughey, S. L., Middleton, S., & Cretchley, J. (2011). The evolution of the international business field: A scientometric investigation of articles published in its premier journal. Scientometrics, 88(1), 17–42.

    Article  Google Scholar 

  • Lonner, W. J., Smith, P. B., van de Vijver, F. J., & Murdock, E. (2010). Entering our fifth decade: An analysis of the influence of the Journal of Cross-Cultural Psychology during its first forty years of publication. Journal of Cross-Cultural Psychology, 41(3), 301–317.

    Article  Google Scholar 

  • Marsh, E. E., & White, M. D. (2006). Content analysis: A flexible methodology. Library trends, 55(1), 22–45.

  • Mustafee, N., Katsaliaki, K., & Fishwick, P. (2014). Exploring the modelling and simulation knowledge base through journal co-citation analysis. Scientometrics, 98(3), 2145–2159.

    Article  Google Scholar 

  • Noltemeyer, A. L., Proctor, S. L., & Dempsey, A. (2013). Race and ethnicity in school psychology publications: A content analysis and comparison to publications in related disciplines. Contemporary School Psychology, 17(1), 129–142.

    Google Scholar 

  • Padilla, J. J., Diallo, S. Y., & Tolk, A. (2011). Do we need M&S Science? SCS M&S Magazine, 8, 161–166.

    Google Scholar 

  • Poser, C., Guenther, E., & Orlitzky, M. (2012). Shades of green: using computer-aided qualitative data analysis to explore different aspects of corporate environmental performance. Journal of Management Control, 22(4), 413–450.

    Article  Google Scholar 

  • Sagar, A., Kademani, B. S., & Bhanumurthy, K. (2013). Research trends in agricultural science: A global perspective. Journal of Scientometric Research, 2(3), 185.

    Google Scholar 

  • Sarjoughian, H. S., & Zeigler, B. P. (2001). Towards making modeling & simulation into a discipline. Simulation Series, 33(2), 130–135.

    Google Scholar 

  • Schredl, M., Ciric, P., Bishop, A., Gölitz, E., & Buschtöns, D. (2003). Content analysis of German students’ dreams: Comparison to American findings. Dreaming, 13(4), 237–243.

    Article  Google Scholar 

  • Smith, A. E., & Humphreys, M. S. (2006). Evaluation of unsupervised semantic mapping of natural language with Leximancer concept mapping. Behavior Research Methods, 38(2), 262–279.

    Article  Google Scholar 

  • Sokolowski, J. A., & Banks, C. M. (2010a). Modeling and simulation fundamentals: theoretical underpinnings and practical domains. HoBoKen, NJ: Wiley.

    Book  Google Scholar 

  • Sokolowski, J. A., & Banks, C. M. (2010b). The Geometric Growth of M&S Education: Pushing Forward, Pushing Outward. SCS M&S Magazine, 1(4), 1–5.

  • Stemler, S. (2001). An overview of content analysis. Practical assessment, research & evaluation, 7(17), 137–146.

    Google Scholar 

  • Tolk, A. (2010). Engineering management challenges for applying simulation as a green technology. In Proceedings of the 31st Annual National Conference of the American Society for Engineering Management (ASEM) (pp. 137–147). Fayetteville, AR: American Society for Engineering Management.

  • Tse, D. K., Belk, R. W., & Zhou, N. (1989). Becoming a consumer society: A longitudinal and cross-cultural content analysis of print ads from Hong Kong, the People’s Republic of China, and Taiwan. Journal of consumer research, 15(4), 457–472.

    Article  Google Scholar 

  • United States General Accounting Office (1996). Content Analysis: A Methodology for Structuring and Analyzing Written Material. GAO/PEMD-10.3. 1. Washington, DC.

  • Weber, R. P. (Ed.). (1990). Basic content analysis (No. 49). Beverly Hills: Sage.

    Google Scholar 

  • Welvaert, M., & Rosseel, Y. (2014). A review of FMRI simulation studies. Plos One, 9(7), e101953.

    Article  Google Scholar 

  • Wierzbicki, A. P. (2007). Modelling as a way of organising knowledge. European Journal of Operational Research, 176(1), 610–635.

    Article  MATH  Google Scholar 

  • Wiitavaara, B., Björklund, M., Brulin, C., & Djupsjöbacka, M. (2009). How well do questionnaires on symptoms in neck-shoulder disorders capture the experiences of those who suffer from neck-shoulder disorders? A content analysis of questionnaires and interviews. BMC Musculoskeletal Disorders, 10(1), 30.

    Article  Google Scholar 

  • Yilmaz, L., Davis, P., Fishwick, P., Hu, X., Miller, J., Hybinette, M., Oren, T., Reynolds, P., Sarjoughian, H. & Tolk, A. (2008). What makes good research in modeling and simulation: Sustaining the growth and vitality of the M&S discipline. In Proceedings of the 40th Conference on Winter Simulation (pp. 677–688). Miami, FL: Winter Simulation Conference.

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Acknowledgments

We would like to acknowledge and thank the ACM Digital Library for granting us permission to use their archives. We would like to acknowledge friends and colleagues who have helped by providing their perspective on their own discipline and how they use M&S.

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Correspondence to Saikou Y. Diallo.

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Diallo, S.Y., Gore, R.J., Padilla, J.J. et al. An overview of modeling and simulation using content analysis. Scientometrics 103, 977–1002 (2015). https://doi.org/10.1007/s11192-015-1578-6

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  • DOI: https://doi.org/10.1007/s11192-015-1578-6

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