Document Type : Articles


1 Assistant Prof., Research Department of Information Management, Islamic World Science & Technology Monitoring and Citation Institute (ISC), Shiraz, Iran

2 PhD in Knowledge and Information Science (Information Retrieval), Director of Statistics and Information Technology, Gonabad University of Medical Sciences, Gonbad, Iran.


Publications on knowledge and information creation have grown significantly due to their importance in information and knowledge management. This study aims to discover and analyze the hidden thematic topics of information and knowledge creation publications. The research applied was performed using text mining techniques and an analytical approach. The research population comprises publications on knowledge and information creation from 1900 to 2021, retrieved from the Web of Science Core Collection (WOSCC). The data were analyzed by Latent Dirichlet Allocation (LDA) algorithm and Python Programming Language. Forty-eight thousand two hundred sixty-five documents were retrieved and analyzed. "Data production," "Health seeking behavior," "Human Brain and Information processing," "Decision-making models," "Knowledge production," "Information needs," and "Digital Literacy" are among the essential topics in order of publication rate. The results indicated that the spectrum of the fourteen topics covered a variety of dimensions, including "data and knowledge creation," "information processing," "information needs and behavior," "digital literacy," and "critical thinking." The study's findings have shown the conceptual relationships between textual data and the presentation of the knowledge structure of information and knowledge creation. Based on this, it can be concluded that the creation of knowledge and information includes human mental and behavioral processes concerning knowledge.


Alghamdi, R. & Alfalqi, K. (2015). A survey of topic modeling in text mining. International Journal of Advanced Computer Science and Applications (IJACSA), 6(1), 147-153. Retrieved from
Allcott, H. &Taubinsky, D. (2015). Evaluating behaviorally motivated policy: Experimental evidence from the lightbulb market. American Economic Review, 105(8), 2501-2538.
Anderson, B.S. (2021). Using text mining to glean insights from COVID-19 literature. Journal of Information Science, 49(2), 373-381.
Arrom, L.M., Huguet, J., Errando, C., Breda, A.& Palou, J. (2018). How to write an original article. Actas Urológicas Españolas (English Edition), 42(9), 545-550.
Baghmohammad, M., Mansouri, A. & CheshmehSohrabi, M. (2021). Identification of topic development process of knowledge and information science field based on the topic modelling (LDA). Iranian Journal of Information Processing and Management, 36(2), 297-326. [in Persian]
Baker, K.S. & Mayernik, M.S. (2020). Disentangling knowledge production and data production. Ecosphere, 11(7), e03191.
Bates, M.J. (2010). Information behavior. Encyclopedia of library and information sciences, 3, 2381-2391.
Blei, D.M., Ng, A.Y. & Jordan, M.I. (2003). Latent Dirichlet allocation. Journal of Machine Learning Research, 3(Jan), 993-1022. Retrieved from
Blei, D.M. (2012). Probabilistic topic models. Communications of the ACM, 55(4), 77-84.
Broussard, R. & Doty, P. (2016). Toward an understanding of fiction and information behavior. Proceedings of the Association for Information Science and Technology, 53(1), 1-10.
Cao, G., Duan, Y. & Cadden, T. (2019). The link between information processing capability and competitive advantage mediated through decision-making effectiveness. International Journal of Information Management, 44, 121-131.
Cao, G., Duan, Y. & Li, G. (2015). Linking business analytics to decision-making effectiveness: A path model analysis. IEEE Transactions on Engineering Management, 62(3), 384-395.
Chen, B., Tsutsui, S., Ding, Y. & Ma, F., 2017. Understanding the topic evolution in a scientific domain: An exploratory study for the field of information retrieval. Journal of Informetrics, 11(4), 1175-1189.
Chen, X., Zou, D. & Xie, H. (2020). Fifty years of British Journal of Educational Technology: A topic modelling based bibliometric perspective. British Journal of Educational Technology, 51(3), 692-708.
Clemons, E.K. (2008). How information changes consumer behavior and how consumer behavior determines corporate strategy. Journal of management information systems, 25(2),13-40.
Cutrona, S.L., Mazor, K.M., Vieux, S.N., Luger, T.M., Volkman, J.E. & Finney Rutten, L.J. (2015). Health information-seeking on behalf of others: characteristics of surrogate seekers. Journal of Cancer Education, 30(1), 12-19.
Danesh, F., Dastani, M. & Ghorbani, M. (2021). Retrospective and prospective approaches of coronavirus publications in the last half-century: A Latent Dirichlet allocation analysis. Library Hi Tech, 39(3), 855-872.
Dastani, M. & Danesh, F. (2021). Iranian COVID-19 publications in LitCovid: Text mining and topic modeling. Scientific Programming, 1-12. Article ID 3315695,
Dastani, M., Mousavi chelak, A., Ziaei, S. & Delghandi, F. (2020). Topic analysis of published articles in medical librarianship and information science in iran using text mining techniques. Depiction of Health, 11(4),355-367. [in Persian]
Ennis, R.H. (2015). Critical thinking: A streamlined conception. In The Palgrave handbook of critical thinking in higher education (pp. 31-47). Palgrave Macmillan, New York.
Fan, W., Wallace, L., Rich, S. & Zhang, Z. (2006). Tapping the power of text mining. Communications of the ACM, 49(9),76-82.
Fiandrino, S. & Tonelli, A. (2021). A text-mining analysis on the review of the non-financial reporting directive: bringing value creation for stakeholders into accounting. Sustainability, 13(2),763.
Figuerola, C. G., García Marco, F. J. & Pinto, M. (2017). Mapping the evolution of library and information science (1978-2014) using topic modelling on LISA. Scientometrics, 112(3),1507-1535.
Goldman, S.R. & Scardamalia, M. (2013). Managing, understanding, applying, and creating knowledge in the information age: Next-generation challenges and opportunities. Cognition and Instruction, 31(2),255-269.
Gorichanaz, T. (2019). Information creation and models of information behavior: Grounding synthesis and further research. Journal of Librarianship and Information Science, 51(4), 998-1006.
Griffin, R.J., Dunwoody, S. & Neuwirth, K. (1999). Proposed model of the relationship of risk information seeking and processing to the development of preventive behaviors. Environmental Research, 80(2),S230-S245.
Halevy, A., Norvig, P. & Pereira, F. (2009). The unreasonable effectiveness of data. IEEE Intelligent Systems, 24(2), 8-12.
Han, X. (2020). Evolution of research topics in LIS between 1996 and 2019: An analysis based on latent Dirichlet allocation topic model. Scientometrics, 125(3), 2561-2595.
Hannigan, T.R., Haans, R.F., Vakili, K., Tchalian, H., Glaser, V.L., Wang, M.S., Kaplan, S. and Jennings, P.D. (2019). Topic modelling in management research: Rendering new theory from textual data. Academy of Management Annals, 13(2), 586-632.
Huang, M., Zhang, H., Gu, Y., Wei, J., Gu, S., Zhen, X., Hu, X., Sun, X. & Dong, H. (2019). Outpatient health-seeking behavior of residents in Zhejiang and Qinghai Province, China. BMC Public Health, 19(1),1-8. Retrieved from
Huvila, I. (2011). The complete information literacy? Unforgetting creation and organization of information. Journal of Librarianship and Information Science, 43(4), 237-245.
Huvila, I., Douglas, J., Gorichanaz, T., Koh, K. & Suorsa, A. (2022). Guest editorial: Advances in research on information creation. Library & Information Science Research, 44(3), 101178.
Indurkhya, N. & Damerau, F.J., 2010. Handbook of natural language processing. Chapman and Hall/CRC.
Jelodar, H., Wang, Y., Yuan, C., Feng, X., Jiang, X., Li, Y. & Zhao, L. (2019). Latent Dirichlet Allocation (LDA) and topic modelling: models, applications, a survey. Multimedia Tools and Applications, 78(11),15169-15211.
Jung, H. & Kim, B. (2021). Identifying research topics and trends in asset management for sustainable use: A topic modeling approach. Sustainability, 13(9),4792.
Kari, J., 2007. Conceptualizing the personal outcomes of information. Information Research, 12(2). Retrieved from
Kari, J., (2011). Outcomes of information: An analysis of spiritual messages. The Open Information Science Journal, 3, 63-75.
Katre, P. D. (2019, December). Text mining and comparative visual analytics on large collection of speeches to trace socio-political issues. In 2019 IEEE 9th International Conference on Advanced Computing (IACC) (pp. 108-114). IEEE.
Kobayashi, V.B., Mol, S.T., Berkers, H.A., Kismihók, G. & Den Hartog, D.N. (2018). Text classification for organizational researchers: A tutorial. Organizational Research Methods, 21(3),766-799.
Koh, K. (2013). Adolescents' information‐creating behavior embedded in digital Media practice using scratch. Journal of the American Society for Information Science and Technology, 64(9),1826-1841.
Kurata, K., Miyata, Y., Ishita, E., Yamamoto, M., Yang, F. & Iwase, A. (2018). Analyzing library and information science full‐text articles using a topic modelling approach. Proceedings of the Association for Information Science and Technology, 55(1),847-848.
Lamba, M. & Madhusudhan, M. (2019). Mapping of topics in DESIDOC Journal of Library and Information Technology, India: A study. Scientometrics, 120(2), 477-505.
Lee, L., Ocepek, M.G. & Makri, S. (2021). Creating by me, and for me: investigating the use of information creation in everyday life. Information Research, 26(1). Retrieved from
Linder, R., Snodgrass, C. & Kerne, A. (2014, April). Everyday ideation: All of my ideas are on Pinterest. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 2411-2420).
Lund, N.W. & Skare, R. (2009). Document theory. Annual Review of Information Science and Technology, 43(1), 1-55.
Martin, A. & Madigan, D. eds., (2006). Digital literacies for learning. Facet Publishing.
Miyata, Y., Ishita, E., Yang, F., Yamamoto, M., Iwase, A. & Kurata, K. (2020). Knowledge structure transition in library and information science: Topic modelling and visualization. Scientometrics, 125(1), 665-687.
Multas, A.M. & Hirvonen, N. (2021). "Let's keep this video as real as possible": young video bloggers constructing cognitive authority through a health-related information creation process. Journal of Documentation, 78(7), 42-64.
Park, J.H. & Song, M. (2013). A study on the research trends in library & information science in Korea using topic modeling. Journal of the Korean society for information management, 30(1),7-32. [in korean]
Paul, R. (1995). Critical thinking: How to prepare students for a rapidly changing world. Foundation for Critical Thinking: Santa Rosa, CA
Preum, S.M., Clark, K., Davis, A., Khutsishvilli, K. and Valdez, R.S. (2019). Information seeking and information processing behaviors among Type 2 diabetics. arXiv preprint arXiv:1910.12444
Ransbotham, S., Kiron, D. and Prentice, P.K. (2016). Beyond the hype: The hard work behind analytics success. MIT Sloan Management Review, 57(3).
 Řehůřek, R. & Sojka, P. (2010). Software framework for topic modelling with large corpora. In Proceedings of the LREC 2010 workshop on new challenges for NLP frameworks.
Robson, A. & Robinson, L. (2013). Building on models of information behaviour: linking information seeking and communication. Journal of documentation, 69(2), 169-193.
Röder, M., Both, A. & Hinneburg, A. (2015, February). Exploring the space of topic coherence measures. In Proceedings of the Eighth ACM International Conference on Web Search and Data Mining (pp. 399-408).
Rosenbaum, S. (2011). Curation nation: How to win in a world where consumers are creators. McGraw Hill Professional.
Rousselet, G.A., Thorpe, S.J. & Fabre-Thorpe, M. (2004). How parallel is visual processing in the ventral pathway? Trends in cognitive Sciences, 8(8),363-370.
Schmiedel, T., Müller, O. & vom Brocke, J. (2019). Topic modelling as a strategy of inquiry in organizational research: A tutorial with an application example on organizational culture. Organizational Research Methods, 22(4), 941-968.
Sievert, C. & Shirley, K. (2014, June). LDAvis: A method for visualizing and interpreting topics. In Proceedings of the workshop on interactive language learning, visualization, and interfaces (pp. 63-70).
 Syed, S. & Spruit, M. (2017, October). Full-text or abstract? examining topic coherence scores using latent dirichlet allocation. In 2017 IEEE International Conference on Data Science and Advanced Analytics (DSAA) (pp. 165-174). IEEE.
Trace, C. B. (2007). Information creation and the notion of membership. Journal of Documentation, 63(1), 142-163.
 Von Neumann, J. (2012). The computer and the brain. Yale University Press.
 Wang, M. & Mengoni, P. (2020, December). How pandemic spread in news: Text analysis using topic model. In 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) (pp. 764-770). IEEE.
 Whittaker, S. (2011). Personal information management: from information consumption to curation. Annual Review of Information Science and Technology, 45(1).
 Wickens, C.D. & Carswell, C.M. (2021). Information processing. In Handbook of human factors and ergonomics,117-151. John Wiley & Sons, INC. retrived from
 Wilson, T.D. (2000). Human information behavior. Informing Science, 3(2), 49-56. Retrived from
 Wilson, V.L. (2009). Behavioral change in type 1 diabetes self-management: Why and how? Health Education Journal, 68(4), 320-327.
World Health Organization (2021). Infodemic management: a key component of the COVID-19 global response. Weekly Epidemiological Record, 145-148.
Woxland, C. M., Cochran, D., Davis, E. L. & Lundstrom, K. (2017). Communal and student-centered: Teaching information creation as a process with mobile technologies. Reference Services Review, 45(1), 79-99.
 Yan, E. (2014). Research dynamics: Measuring the continuity and popularity of research topics. Journal of Informetrics, 8(1), 98-110.
 Yan, E. (2015). Research dynamics, impact, and dissemination: A topic‐level analysis. Journal of the Association for Information Science and Technology, 66(11), 2357-2372.