Participatory cultural mapping based on collective behavior data in location-based social networks

Abstract : Culture has been recognized as a driving impetus for human development. It co-evolves with both human belief and behavior. When studying culture, Cultural Mapping is a crucial tool to visualize different aspects of culture (e.g., religions and languages) from the perspectives of indigenous and local people. Existing cultural mapping approaches usually rely on large-scale survey data with respect to human beliefs, such as moral values. However, such a data collection method not only incurs a significant cost of both human resources and time, but also fails to capture human behavior, which massively reflects cultural information. In addition, it is practically difficult to collect large-scale human behavior data. Fortunately, with the recent boom in Location-Based Social Networks (LBSNs), a considerable number of users report their activities in LBSNs in a participatory manner, which provides us with an unprecedented opportunity to study large-scale user behavioral data. In this article, we propose a participatory cultural mapping approach based on collective behavior in LBSNs. First, we collect the participatory sensed user behavioral data from LBSNs. Second, since only local users are eligible for cultural mapping, we propose a progressive "home" location identification method to filter out ineligible users. Third, by extracting three key cultural features from daily activity, mobility, and linguistic perspectives, respectively, we propose a cultural clustering method to discover cultural clusters. Finally, we visualize the cultural clusters on the world map. Based on a real-world LBSN dataset, we experimentally validate our approach by conducting both qualitative and quantitative analysis on the generated cultural maps. The results show that our approach can subtly capture cultural features and generate representative cultural maps that correspond well with traditional cultural maps based on survey data
Type de document :
Article dans une revue
ACM transactions on intelligent systems and technology (TIST), 2016, 7 (3), pp.1 - 23. 〈10.1145/2814575〉
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https://hal.archives-ouvertes.fr/hal-01346717
Contributeur : Médiathèque Télécom Sudparis & Institut Mines-Télécom Business School <>
Soumis le : mardi 19 juillet 2016 - 14:49:48
Dernière modification le : jeudi 15 novembre 2018 - 11:59:01

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Dingqi Yang, Daqing Zhang, Bingqing Qu. Participatory cultural mapping based on collective behavior data in location-based social networks. ACM transactions on intelligent systems and technology (TIST), 2016, 7 (3), pp.1 - 23. 〈10.1145/2814575〉. 〈hal-01346717〉

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