Supporting the below United Nations Sustainable Development Goals:支持以下聯合國可持續發展目標：支持以下联合国可持续发展目标：
Examination Committee
Prof Wai Ho MOW, ECE/HKUST (Chairperson)
Prof James SHE, ECE/HKUST (Thesis Supervisor)
Prof Matthew MCKAY, ECE/HKUST
Abstract
Many news media these days have utilized mobile applications to deliver news and information to their target audience ubiquitously by push notification technology. In this research, a dataset with 240 million records about mobile notification activities of 1.8 million users from a major local mobile news application, Apple Daily, was analyzed.
A big data analytic framework for effective mobile notification delivery is designed to optimize users’ average opening rate of and response time to these mobile notifications. A model is first introduced to quantify the effectiveness of mobile notifications in terms of the notification opening rate of users. Some novel analytic approaches to send more relevant mobile notification to users based on their content and location are proposed to optimize such effectiveness. The results of the proposed analytic framework have proved that the average opening rate of the pushed notification can be increased up to 62%, and the corresponding response times can be reduced up to 17%. To the best of our knowledge, this analytic research is the first attempt in the related field to optimize the effectiveness of mobile notifications for news and information delivery.