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다국어 초록 (Multilingual Abstract)

This study proposed an approach of clustering collective users’ activities of location-based social networks using check-in data of Foursquare users in Seoul. In order to cluster the collective activities, we generated sequential rules of the activities using sequential rule mining, and then constructed activity networks based on the rules. We analyzed the activity networks to identify network structure and hub activities, and clustered the activities within the networks. Unlike previous studies that analyzed activity transition patterns of location-based social network users, this study focused on analyzing the structure and clusters of successive activities. Hubs and clusters of activities with the approach proposed in this study can be used for location-based services and marketing. They could also be used in the public sector, such as infection prevention and urban policies.

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참고문헌 (Reference)

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