運用資料探勘技術預測分析持續互動性高之粉絲團：以臉書醫療健康粉絲團為例

Predicting Activeness of Medical and Healthcare Fan Page on Facebook Using Data Mining Techniques

李珮如(Pei-Ju Lee) ； 胡雅涵(Ya-Han Hu) ； 李彥賢(Yen-Hsien Lee) ； 吳俊霆(Chun-Ting Wu)

《電子商務學報》 23卷1期 (2021/06) Pp. 71-95

https://doi.org/10.6188/JEB.202106_23(1).0004

摘要

Facebook開放粉絲團功能後，公司機構的粉絲團數有漸增趨勢；研究指出在粉絲團上鼓勵用戶間互動或與粉絲團經營者互動，將有助提升用戶滿意度，進而增進品牌忠誠度。社群媒體亦常用於增加醫療機構或醫師曝光度、及患者與醫療人員或其他患者即時的線上溝通。過去研究未以維持醫療健康粉絲團人數與忠誠度為主軸，且社群網站特性如用戶互動情況等，在醫療健康粉絲團經營上也未被重視。本研究以用戶互動及貼文類型等變數，使用資料探勘方法找出擁有相對高活躍率粉絲團之共同因子，預測粉絲團是否能維持活躍度，以提供醫療機構維持用戶之參考。實驗結果顯示提高貼文頻率、以照片或影片貼文為主、注重貼文反應及訪客貼文內容，將有較高之醫療健康粉絲團活躍率。

關鍵字

Facebook ； 粉絲團 ； 診所 ； 資料探勘

並列摘要

The launch of fan page on Facebook has encouraged businessies and organizations to create and operate their respective fan pages. Previous research indicated that users' satisfactions and loyalties can be enhanced by encouraging interations among users (fans) or with curators of the fan page. Social media such as Facebook is often used to increase the exposure of medical institutions or physicians, and to provide a platform for users to communicate directly and immediately with medical staffs or other patients. However, the prior research did not focus on the retention of user and the enhancement of loyalty on medical or healthcare fan pages; in addition, the characteristics of social network sites such as user interactions and connections were not taken into consideration in the operation of medical and healthcare fan pages. Therefore, this study uses data mining techniques to identify important factors of highly active fan pages, and to predict fan pages that could remain active. Our observations provide suggestions for medical and healthcare institutions in retaining users. The experiment results indicate that medical and healthcare fan pages could remain active by increasing the post frequency, incorporating photos or videos in the post, responding to the posts and comments actively.

並列關鍵字

Facebook ； fan page ； clinic ； data mining

參考文獻

Alshaikh, F., Ramzan, F., Rawaf, S., & Majeed, A. (2014). Social network sites as a mode to collect health data: A systematic review. Journal of Medical Internet Research, 16(7), e171. Retrieved Januray 4, 2016, from https://www.jmir.org/2014/7/e171/PDF

Bagnied, M., Speece, M., & Pongpaew, W. (2016). Corporate Facebook and customer brand engagement in Kuwait. Proceedings of the 2016 Global Marketing Conference, Hong Kong.

Beukeboom, C. J., Kerkhof, P., & de Vries, M. (2015). Does a virtual like cause actual liking? How following a brand's Facebook updates enhances brand evaluations and purchase intention. Journal of Interactive Marketing, 32, 26-36.

Boyd, D. M., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1), 210-230.

Bozkir, A. S., Mazman, S. G., & Sezer, E. A. (2010). Identification of user patterns in social networks by data mining techniques: Facebook case. Proceedings of the International Symposium on Information Management in a Changing World, Ankara, Turkey.