Predicting the Number of Clicks in a Local Information Sharing System Focusing on Generational Information

Abstract

In recent years, “Tame-map” has emerged as a social media platform for local revitalization. It is a web application for sharing local information. It enables users to conveniently post and view information on local events in their daily lives. Because many “Tame-map” users are likely to participate in events, increasing the number of views is an important issue from the perspective of regional revitalization. The design relies on the organizer’s experience and intuition, and there is no established method for developing a design that attracts a large number of viewers. Therefore, if the number of visitors can be predicted in advance, it is feasible to reconsider the design of flyers based on this information. In addition, in click-through rate (CTR) prediction, which is an aspect of advertising analysis, it has been revealed that predicting the user attributes of viewers contributes to improving the prediction accuracy. However, in the “Tame-map” system, user attributes of viewers do not exist. In this study, we aim to clarify the extent to which considering the generational tags assigned to events would impact the prediction of click counts.