Abstract
The purpose of this study is to conduct a thematic analysis of Twitter-related publications in knowledge management (KM) discipline and explore different research themes of KM Twitter-related publications. These publications were retrieved from Web of Science (WoS) during time span of 2009–2020 and thematic analysis was conducted through VOSviewer. Different methodologies were used according to the nature of bibliometric analysis and explained in each section. Three themes were emerged from these publications indicating Twitter users’ explicit contribution in KM through big data and text mining, knowledge sharing through communities’ collaboration and KM through machine learning. This is the first bibliometric study to explore overall contribution of Twitter-related publications in KM field at a glance.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Noor, S., Guo, Y., Shah, S.H.H., Nawaz, M.S., Butt, A.S.: Research synthesis and thematic analysis of twitter through bibliometric analysis. Int. J. Semant. Web Inform. Syst. (2019, forthcoming)
Fausto, S., Aventurier, P.: Scientific literature on Twitter as a subject research: findings based on bibliometric analysi. Handb. Twitter Res. 2015 (2016). https://doi.org/10.5281/zenodo.44882
Kapoor, K.K., Tamilmani, K., Rana, N.P., Patil, P., Dwivedi, Y.K., Nerur, S.: Advances in social media research: past, present and future. Inform. Syst. Front. 20(3), 531–558 (2017). https://doi.org/10.1007/s10796-017-9810-y
Chen, X., Wang, S., Tang, Y., Hao, T.: A bibliometric analysis of event detection in social media. Online Inf. Rev. 43(1), 29–52 (2019). https://doi.org/10.1108/OIR-03-2018-0068
Zyoud, S.H., Sweileh, W.M., Awang, R., Al-Jabi, S.W.: Global trends in research related to social media in psychology: mapping and bibliometric analysis. Int. J. Ment. Health Syst. 12(1), 4 (2018). https://doi.org/10.1186/s13033-018-0182-6
Noor, S., Guo, Y., Shah, S., Halepoto, H.: Bibliometric Analysis of Twitter Knowledge Management Publications Related to Health Promotion. In: Li, G., Shen, H.T., Yuan, Y., Wang, X., Liu, H., Zhao, X. (eds.) KSEM 2020. LNCS (LNAI), vol. 12274, pp. 341–354. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-55130-8_30
Ford, D.P., Mason, R.M.: A multilevel perspective of tensions between knowledge management and social media. J. Organ. Comput. Electron. Commer. 23(1–2), 7–33 (2013). https://doi.org/10.1080/10919392.2013.748604
Nisar, T.M., Prabhakar, G., Strakova, L.: Social media information benefits, knowledge management and smart organizations. J. Bus. Res. 94, 264–272 (2019). https://doi.org/10.1016/j.jbusres.2018.05.005
Scuotto, V., Del Giudice, M., Omeihe, K.: SMEs and mass collaborative knowledge management: toward understanding the role of social media networks. Inform. Syst. Manag. 34(3), 280–290 (2017). https://doi.org/10.1080/10580530.2017.1330006
Sigala, M., Chalkiti, K.: Knowledge management, social media and employee creativity. Int. J. Hosp. Manag. 45, 44–58 (2015). https://doi.org/10.1016/j.ijhm.2014.11.003
Shah, S.H.H., Lei, S., Ali, M., Doronin, D., Hussain, S.T.: Prosumption: bibliometric analysis using HistCite and VOSviewer. Kybernetes 49(3), 1–24 (2019). https://doi.org/10.1108/K-12-2018-0696
Shah, S.H.H., Noor, S., Ahmad, A.B., Butt, A.S., Lei, S.: Retrospective view and thematic analysis of value co-creation through bibliometric analysis. Total Qual. Manag. Bus. Excell., 1–25 (2021). https://doi.org/10.1080/14783363.2021.1890017
Noor, S., Guo, Y., Shah, S., Philippe Fournier-Viger, M., Nawaz, S.: Analysis of public reactions to the novel coronavirus (COVID-19) outbreak on Twitter. Kybernetes 50(5), 1633–1653 (2020). https://doi.org/10.1108/K-05-2020-0258
Pritchard, A.: Statistical bibliography or bibliometrics? J. Doc. 25(4), 348–349 (1969)
Van Eck, N.J., Waltman, L.: Appropriate similarity measures for author co-citation analysis. J. Am. Assoc. Inform. Sci. Technol. 59(10), 1653–1661 (2008). https://doi.org/10.1002/asi.20872
Noor, S., Guo, Y., Shah, S., Saqib Nawaz, M., Butt, A.: Bibliometric analysis of social media as a platform for knowledge management. Int. J. Knowl. Manag. 16(3), 33–51 (2020). https://doi.org/10.4018/IJKM.2020070103
Decker, R., Lenz, H.-J. (eds.): Advances in Data Analysis. SCDAKO, Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-70981-7
Shah, S.H.H., Lei, S., Noor, S., Anjum, A.: Research synthesis and new directions of prosumption: a bibliometric analysis. Int. J. Inform. Manag. Sci. 31(1), 79–98 (2020). https://doi.org/10.6186/IJIMS.20200331(1).0005
Nicolas-Rocca, T., Parrish, J.: Capturing and conveying chamorro cultural knowledge using social media. Int. J. Knowl. Manag. 9(3), 1–18 (2013). https://doi.org/10.4018/ijkm.2013070101
Zhao, Y.W., van den Heuvel, W.-J., Ye, X.: Exploring Big Data in Small Forms: A Multi-layered Knowledge Extraction of Social Networks (2013)
Wang, W., Chen, L., Thirunarayan, K., Sheth, A.P.: Harnessing Twitter ‘big data’ for automatic emotion identification. In: Proceedings – 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust and 2012 ASE/IEEE International Conference on Social Computing, SocialCom/PASSAT 2012, pp. 587–592 (2012). https://doi.org/10.1109/SocialCom-PASSAT.2012.119
Okazaki, S., Díaz-Martín, A.M., Rozano, M., Menéndez-Benito, H.D.: Using twitter to engage with customers: a data mining approach. Internet Res. 25(3), 416–434 (2015). https://doi.org/10.1108/IntR-11-2013-0249
Huang, Y., Zhou, S., Huang, K., Guan, J.: Boosting Financial Trend Prediction with Twitter Mood Based on Selective Hidden Markov Models. In: Renz, M., Shahabi, C., Zhou, X., Cheema, M.A. (eds.) DASFAA 2015. LNCS, vol. 9050, pp. 435–451. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-18123-3_26
Aghababaei, S., Makrehchi, M.: Mining Twitter data for crime trend prediction. Intell. Data Anal. 22(1), 117–141 (2018). https://doi.org/10.3233/IDA-163183
Valencia-García, R., Lagos-Ortiz, K., Alcaraz-Mármol, G., del Cioppo, J., Vera-Lucio, N. (eds.): CITI 2016. CCIS, vol. 658. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-48024-4
Chaudhry, A.S.: Use of Social Media and Networks to Support Personal Knowledge Management: A Study of PKM Practices of Government Officers in Kuwait, pp. 136–139 (2013)
Kreiner, K., Immonen, A., Suominen, H.: Crisis Management Knowledge from Social Media, pp. 105–108 (2013). https://doi.org/10.1145/2537734.2537740
Panahi, S., Watson, J., Partridge, H.: Information encountering on social media and tacit knowledge sharing. J. Inform. Sci. 42(4), 539–550 (2016). https://doi.org/10.1177/0165551515598883
Abu-Salih, B., Wongthongtham, P., Kit, C.: Twitter mining for ontology-based domain discovery incorporating machine learning. J. Knowl. Manag. 22(5), 949–981 (2018). https://doi.org/10.1108/JKM-11-2016-0489
Wang, A.H.: Detecting Spam Bots in Online Social Networking Sites: A Machine Learning Approach. In: Foresti, S., Jajodia, S. (eds.) DBSec 2010. LNCS, vol. 6166, pp. 335–342. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-13739-6_25
Porshnev, A., Redkin, I., Shevchenko, A.: Machine learning in prediction of stock market indicators based on historical data and data from twitter sentiment analysis. In: Proceedings - IEEE 13th International Conference on Data Mining Workshops, ICDMW 2013 pp. 440–444 (2013). https://doi.org/10.1109/ICDMW.2013.111
Kassens-Noor, E.: Twitter as a teaching practice to enhance active and informal learning in higher education: The case of sustainable tweets. Act. Learn. High. Educ. 13(1), 9–12 (2012). https://doi.org/10.1177/1469787411429190
Menkhoff, T., Chay, Y., Bengtsson, M., Jason Woodard, C., Gan, B.: Incorporating microblogging (“tweeting”) in higher education: lessons learnt in a knowledge management course. Comput. Human Behav. 51, 1295–1302 (2015). https://doi.org/10.1016/j.chb.2014.11.063
Funding
This research is financially supported by The National Key Research and Development Program of China (grant number 2018YFC0807105), National Natural Science Foundation of China (grant number 61462073) and Science and Technology Committee of Shanghai Municipality (STCSM) (under grant numbers 17DZ1101003, 18511106602 and 18DZ2252300).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Ethics declarations
The authors declare no conflict of interest.
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Noor, S., Guo, Y., Shah, S.H.H., Halepoto, H. (2021). Thematic Analysis of Twitter as a Platform for Knowledge Management. In: Qiu, H., Zhang, C., Fei, Z., Qiu, M., Kung, SY. (eds) Knowledge Science, Engineering and Management. KSEM 2021. Lecture Notes in Computer Science(), vol 12817. Springer, Cham. https://doi.org/10.1007/978-3-030-82153-1_50
Download citation
DOI: https://doi.org/10.1007/978-3-030-82153-1_50
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-82152-4
Online ISBN: 978-3-030-82153-1
eBook Packages: Computer ScienceComputer Science (R0)