In this paper, user log data of mobile notificationsare collected from a real mobile news application, and notificationopening rate and reaction time are identified as key parametersthat characterize user behavior. The results indicate that notificationopening patterns depend on the content of notifications, the time at which they are sent, the activeness of users, andthe reaction time. This paper also demonstrates that there existsan inverse relationship between the notification opening rate ofusers and their notification reaction time, and between theirnotification opening rate and notification opening volume. Then, a novel method of quantifying notification usefulness for users isdeveloped, where 3 models are presented to describe usefulnessof notifications against the volume of notifications received, eachrelevant in different contexts. Utilizing this usefulness model, a notification optimization framework is developed for sendingnotifications from different news categories. The optimized notificationallocation improved the average notification opening rateby by 65.24% from 4.92% to 8.13%, and the average reactiontime improved by 13.13% from 20.4 hours to 17.68 hours.