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2017 | OriginalPaper | Chapter

Using Data Mining Strategy in Qualitative Research

Authors : Nadhirah Rasid, Puteri N. E. Nohuddin, Hamidah Alias, Irna Hamzah, A. Imran Nordin

Published in: Advances in Visual Informatics

Publisher: Springer International Publishing

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Abstract

Analyzing qualitative data can be tedious if it is done manually. There are several techniques available to conduct qualitative research such as thematic analysis, grounded theory and content analysis amongst other techniques. The data collected from these techniques are usually huge in amount. Little has been done to apply data mining strategy to analyzes data gathered using qualitative methodology. In this paper, we present a work done to apply text mining technique to analyzes data gathered from interviews – unstructured data. The aim of this study is to develop patterns of pediatric cancer patient’s activities in the ward. The result shows a pattern that suggests patients are mostly playing video games while receiving treatment and when they feel bored in the ward. This proposes that data mining techniques can be used to provide an initial insight of the information gathered qualitatively.

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Woodgate, R.: Part I: an introduction to conducting qualitative research in children with cancer. J. Pediatr. Oncol. Nurs. 17, 192–206 (2000)CrossRef

Rama Prasath, A., Ramya, M.M.: Automated drusen grading system in fundus image using fuzzy c-means clustering. Int. J. Eng. Technol. 6, 833–841 (2014)

Zhu, F., Patumcharoenpol, P., Zhang, C., Yang, Y., Chan, J., Meechai, A., Vongsangnak, W., Shen, B.: Biomedical text mining and its applications in cancer research. J. Biomed. Inform. 46, 200–211 (2013)CrossRef

Katal, A., Wazid, M., Goudar, R.H.: Big data: issues, challenges, tools and good practices. In: 2013 6th International Conference Contemporary Computing, IC3 2013, pp. 404–409 (2013)

Malterud, K.: Qualitative research: standards, challenges, and guidelines. Lancet 358, 483–488 (2001)CrossRef

Zainal, A.O., Nor Saleha, I.T.: National Cancer Registry Report (2011)

Lee, D.W., Kochenderfer, J.N., Stetler-Stevenson, M., Cui, Y.K., Delbrook, C., Feldman, S.A., Fry, T.J., Orentas, R., Sabatino, M., Shah, N.N., Steinberg, S.M., Stroncek, D., Tschernia, N., Yuan, C., Zhang, H., Zhang, L., Rosenberg, S.A., Wayne, A.S., Mackall, C.L.: T cells expressing CD19 chimeric antigen receptors for acute lymphoblastic leukaemia in children and young adults: a phase 1 dose-escalation trial. Lancet 385, 517–528 (2015)CrossRef

Taylor, R.M., Pearce, S., Gibson, F., Fern, L., Whelan, J.: Developing a conceptual model of teenage and young adult experiences of cancer through meta-synthesis. Int. J. Nurs. Stud. 50, 832–846 (2013)CrossRef

Tong, A., Palmer, S., Manns, B., Craig, J.C., Ruospo, M., Gargano, L., Johnson, D.W., Hegbrant, J., Olsson, M., Fishbane, S., Strippoli, G.F.M.: The beliefs and expectations of patients and caregivers about home haemodialysis: an interview study. BMJ Open 3, e002148 (2013)

10.

Wade, D.M., Brewin, C.R., Howell, D.C.J., White, E., Mythen, M.G., Weinman, J.A.: Intrusive memories of hallucinations and delusions in traumatized intensive care patients: an interview study. Br. J. Health. Psychol. 20, 613–631 (2015)CrossRef

11.

Hrastinski, S., Aghaee, N.M.: How are campus students using social media to support their studies? An explorative interview study. Educ. Inf. Technol. 17, 451–464 (2012)CrossRef

12.

Iosup, A., Epema, D.: An experience report on using gamification in technical higher education. In: Proceedings of 45th ACM Technical Symposium on Computer Science Education, SIGCSE 2014, pp. 27–32 (2014)

13.

Ching, L.: A quantitative investigation of narratives: recycled drinking water. Water Policy 17, 831–847 (2015)CrossRef

14.

Castellani, B., Castellani, J.: Data mining: qualitative analysis with health informatics data. Qual. Health Res. 13, 1005–1018 (2003)CrossRef

15.

Alam, F., Pachauri, S.: Comparative study of J48, Naive Bayes and One-R classification technique for credit card fraud detection using WEKA. Adv. Comput. Sci. Technol. 10, 1731–1743 (2017)

16.

Fan, C., Xiao, F., Wang, S.: Development of prediction models for next-day building energy consumption and peak power demand using data mining techniques. Appl. Energy 127, 1–10 (2014)CrossRef

17.

Slimani, T., Lazzez, A.: Efficient Analysis of Pattern and Association Rule Mining Approaches. arXiv preprint arXiv:1402.2892 (2014)

18.

He, W.: Examining students’ online interaction in a live video streaming environment using data mining and text mining. Comput. Hum. Behav. 29, 90–102 (2013)CrossRef

19.

Nohuddin, P.N.E., Coenen, F., Christley, R., Setzkorn, C.: Detecting temporal pattern and cluster changes in social networks: a study focusing UK cattle movement database. In: Shi, Z., Vadera, S., Aamodt, A., Leake, D. (eds.) Intelligent Information Processing V, IIP 2010. IFIP Advances in Information and Communication Technology, vol. 340, pp. 163–172. Springer, Heidelberg (2010). doi:10.1007/978-3-642-16327-2_22

20.

Vijiyarani, S., Sudha, S.: Disease prediction in data mining technique – a survey. Int. J. Comput. Appl. Inf. Technol. 2, 17–21 (2013)

21.

Ahmed, K., Emran, A.A., Jesmin, T., Mukti, R.F., Rahman, M.Z., Ahmed, F.: Early detection of lung cancer risk using data mining. Asian Pac. J. Cancer Prev. 14, 595–598 (2013)

22.

Eynon, R., Hjorth, I., Yasseri, T., Gillani, N.: Understanding Communication Patterns in MOOCs: Combining Data Mining and qualitative methods. arXiv preprint arXiv:1607.07495 (2016)

23.

Dangare, C.S., Apte, S.S.: Improved study of heart disease prediction system using data mining classification techniques. Int. J. Comput. Appl. 0975–888 47, 44–48 (2012)

24.

Yukselturk, E., Ozekes, S., Türel, Y.K.: Predicting dropout student : an application of data mining methods in an online education program. Eur. J. Open Distance e‐Learning 17, 118–133 (2014)

25.

Khadjeh Nassirtoussi, A., Aghabozorgi, S., Ying Wah, T., Ngo, D.C.L.: Text mining of news-headlines for FOREX market prediction: a multi-layer dimension reduction algorithm with semantics and sentiment. Expert Syst. Appl. 42, 306–324 (2015)CrossRef

26.

He, W., Zha, S., Li, L.: Social media competitive analysis and text mining: a case study in the pizza industry. Int. J. Inf. Manag. 33, 464–472 (2013)CrossRef

27.

Bajaj, K., Pattabiraman, K., Mesbah, A.: Mining questions asked by web developers. In: Proceedings 11th Working Conference Mining Software Repositories - MSR 2014, pp. 112–121 (2014)

28.

Berezina, K., Bilgihan, A., Cobanoglu, C., Okumus, F.: Understanding satisfied and dissatisfied hotel customers: text mining of online hotel reviews. J. Hosp. Mark. Manag. 25, 1–24 (2015)

29.

Khadjeh Nassirtoussi, A., Aghabozorgi, S., Ying Wah, T., Ngo, D.C.L.: Text mining for market prediction: a systematic review. Expert Syst. Appl. 41, 7653–7670 (2014)

30.

Rose, J., Lennerholt, C.: Low cost text mining as a strategy for qualitative researchers. Electron. J. Bus. Res. Method 15, 2–16 (2017)

31.

Yu, C.H., Jannasch-Pennell, A., Digangi, S., Yu, C.H.: Compatibility between text mining and qualitative research in the perspectives of grounded theory, content analysis, and reliability. Qual. Rep. 16, 730–744 (2011)

32.

Berglund, M., Westin, L., Svanstrom, R., Sundler, A.J.: Suffering caused by care patients’ experiences from hospital settings. Int. J. Qual. Stud. Health Well-Being 7, 1–9 (2012)CrossRef

33.

Turnbull, M.: A qualitative investigation into the experiences, perceptions, beliefs and self-care management of people with type 2 diabetes (2015)

34.

Morton, K., Balazinska, M., Grossman, D., Mackinlay, J.: Support the data enthusiast. Proc. VLDB Endow. 7, 453–456 (2014)CrossRef

Title: Using Data Mining Strategy in Qualitative Research
Authors: Nadhirah Rasid
Puteri N. E. Nohuddin
Hamidah Alias
Irna Hamzah
A. Imran Nordin
Publisher: Springer International Publishing
Book: Advances in Visual Informatics
Print ISBN: 978-3-319-70009-0

Electronic ISBN: 978-3-319-70010-6

Copyright Year: 2017
DOI: https://doi.org/10.1007/978-3-319-70010-6_10

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