The Use of Messaging Applications among University Students: A Case at Universiti Kebangsaan Malaysia

  • Authors

    • Rosilah Hassan
    • Sura Khalil Abd
    • Wahiza Wahi
    • Fatin Hazwani Siran
    https://doi.org/10.14419/ijet.v7i3.20.28419
  • Messaging applications, WeChat, WhatsApp, Facebook Messenger, University students

  • Abstract

    Since the introduction of smart phones in 1995 by IBM, more and more applications for communication have been created as the medium to transmit messages and fulfill various needs of Android/iOS users.  Most of messaging applications are free of charge and user-friendly as they support the functions of sending or receiving various types of file. This paper reports on a case study on the use of the most trending and active user messaging apps worldwide, e.g. WhatsApp, Facebook Messenger, and WeChat. WhatsApp, among university students at Universiti Kebangsaan Malaysia (UKM). Data for this study were gathered through the questionnaire distributed to sixty respondents. Findings of this study reveal that majority of the respondents use WhatsApp the most to send and receive messages. Most of them agree that they utilize messaging apps for chatting and discussing group assignments. A large portion of the students agrees that they use slang or abbreviation in messaging apps. 50% of the respondents agree that they received false news or fraud message in messaging apps. Most of the respondents agree that they carry out some research on Google to recognize false news. Most of the respondents agree that they feel negative emotion when waiting for a reply in a very long time. Real time chatting and sending message at no cost are the main reasons for choosing messaging apps. Receiving false news and redundant messages are the major drawbacks of messaging apps perceived by the respondents. In general, most of the respondents agree that the technology of messaging apps bring more advantages than disadvantages to general users.

     

     

  • References

    1. [1] Hassan, R., Rahaman, M. S. A., Mokhtar, M. R., & Aman, A. Mobile accounting version 1. In International Conference on Advanced Communication Technology, ICACT (pp. 697-701). [6488281], (2013).

      [2] Corpuz, J.: Best Messaging Apps. https://www.tomsguide.com/us/pictures-story/654-best-messaging-apps.html, last accessed 2018/4/25.

      [3] Shakeel PM, Manogaran G., “Prostate cancer classification from prostate biomedical data using ant rough set algorithm with radial trained extreme learning neural networkâ€, Health and Technology, 2018:1-9.https://doi.org/10.1007/s12553-018-0279-6

      [4] Azman, H., Salman, A., Razak, N. A., Hussin, S., Hasim, M. S., & Sidin, S. M. Determining critical success factors for ICT readiness in a digital economy: A study from user perspective. Advanced Science Letters, 21(5), 1367-1369. DOI: 10.1166/asl.2015.6032. (2015).

      [5] Walker, L.: The 10 Best Mobile Messaging Apps, https://www.lifewire.com/best-mobile-messaging-apps-2654839, last accessed 2018/4/25.

      [6] Manogaran G, Shakeel PM, Hassanein AS, Priyan MK, Gokulnath C. Machine-Learning Approach Based Gamma Distribution for Brain Abnormalities Detection and Data Sample Imbalance Analysis. IEEE Access. 2018 Nov 9.DOI 10.1109/ACCESS.2018.2878276

      [7] Unuth, N.: What Is Skype and What Is It for?. https://www.lifewire.com/what-is-skype-3426903, last accessed 2018/4/27.

      [8] Yap, C. H. & Tay, Y. C.: Penggunaan WeChat dalam pembelajaran dan pengajaran kursus Pengajaran Kurikulum Bahasa Cina Pelajar PISMP. Jurnal Penyelidikan Tindakan IPGK BL Tahun 2014, 8, 37-45. (2014).

      [9] Statista. 2018a. Most popular global mobile messenger apps 2018, https://www.statista.com/statistics/258749/most-popular-global-mobile-messenger-apps/, last accessed 2018/4/26.

      [10] Sridhar KP, Baskar S, Shakeel PM, Dhulipala VS., “Developing brain abnormality recognize system using multi-objective pattern producing neural networkâ€, Journal of Ambient Intelligence and Humanized Computing, 2018:1-9. https://doi.org/10.1007/s12652-018-1058-y

      [11] Baskar, S., & Dhulipala, V. R., “Biomedical Rehabilitation: Data Error Detection and Correction Using Two Dimensional Linear Feedback Shift Register Based Cyclic Redundancy Checkâ€, Journal of Medical Imaging and Health Informatics, 2018, 8(4), 805-808.

      [12] Statista. 2018b. Number of monthly active WhatsApp users as of 2013-2017, https://www.statista.com/statistics/260819/number-of-monthly-active-whatsapp-users/, last accessed 2018/4/26.

      [13] Statista. 2018c. Facebook Messenger: number of monthly active users 2014-2017, https://www.statista.com/statistics/417295/facebook-messenger-monthly-active-users/, last accessed 2018/4/26.

      [14] Abdul Aziz, N. F., Yahya, Y., & Mukhtar, M. Short messaging system (SMS) framework development: A case study of catfish industry in malaysia. In Proceedings of the 2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011 [6021576] DOI: 10.1109/ICEEI.2011.6021576. (2011).

      [15] Ali, R. J. A., Hassan, R., Mayoof, K. D., & Merza, R. A. K. Enhancing quality of service (QoS) for ipv6 video streaming. Asian Journal of Information Technology, 15(16), 2726-2732. DOI: 10.3923/ajit.2016.2726.2732. (2016).

      [16] Anshu Bhatt, Mohd. Arshad. Impact of WhatsApp on Youth: A Sociology Study. IRA- International Journal of Management & Social Sciences. Vol 4, No 2 (2016)

      [17] Bouhnik, D., & Deshen, M. WhatsApp goes to school: Mobile instant messaging between teachers and students. Journal of Information Technology Education: Research, 13, 217-231.(2014)

      [18] Shakeel, P.M., Tolba, A., Al-Makhadmeh, Zafer Al-Makhadmeh, Mustafa Musa Jaber, “Automatic detection of lung cancer from biomedical data set using discrete AdaBoost optimized ensemble learning generalized neural networksâ€, Neural Computing and Applications,2019,pp1-14.https://doi.org/10.1007/s00521-018-03972-2

      [19] Parker, J., Boase-Jelinek, D. & Herrington, J. Perceptions and reflections: Using Skype chat to build a community of learners. In C. Ho & M. Lin (Eds.), Proceedings of E-Learn 2011--World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 1599-1604). Honolulu, Hawaii, USA: Association for the Advancement of Computing in Education (AACE). (2011).

      [20] Kenneth L. Lichstein et.al. Telehealth Cognitive Behavior Therapy for Coâ€Occurring Insomnia and Depression Symptoms in Older Adults.Journal of Clinical Psychology.2013

      [21] Azman, H., Salman, A., Razak, N. A., Hussin, S., Hasim, M. S., & Hassan, M. A. Menentukan ciri-ciri kematangan digital dalam kalangan pengguna ICT di Malaysia. Jurnal Komunikasi: Malaysian Journal of Communication, 30(1), 23-35. (2014).

      [22] Singh, J.: Mobile messaging through android phones: an empirical study to unveil the reasons behind. International Journal of Multidisciplinary and Current research 2(March/April 2014 issue). (2014)

      [23] Shakeel PM. Neural Networks Based Prediction Of Wind Energy Using Pitch Angle Control. International Journal of Innovations in Scientific and Engineering Research (IJISER). 2014;1(1):33-7.

      [24] JoshuaFogel & ElhamNehmad. Internet social network communities: Risk taking, trust, and privacy concerns.Journal of Computers in Human BehaviorVolume 25, Issue 1, January 2009, Pages 153-160

  • Downloads

  • How to Cite

    Hassan, R., Khalil Abd, S., Wahi, W., & Hazwani Siran, F. (2018). The Use of Messaging Applications among University Students: A Case at Universiti Kebangsaan Malaysia. International Journal of Engineering & Technology, 7(3.20), 925-931. https://doi.org/10.14419/ijet.v7i3.20.28419

    Received date: 2019-03-15

    Accepted date: 2019-03-15