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Understanding the behavioral differences between american and german users: A data-driven study
| Title | Understanding the behavioral differences between american and german users: A data-driven study |
| Publication Type | Journal Article |
| Year of Publication | 2018 |
| Authors | Yang, C., Y. Chen, Q. Gong, X. He, Y. Xiao, Y. Huang, and X. Fu |
| Journal | Big Data Mining and Analytics |
| Volume | 1 |
| Pagination | 284-296 |
| Date Published | December |
| ISSN | 2096-0654 |
| Keywords | American users, behavioral characteristics, behavioral data, behavioral difference, behavioral differences, Big Data, Business, Cultural differences, data-driven study, Europe, German users, learning (artificial intelligence), machine learning, online social networks, pattern classification, review styles, social aspects of automation, social connectivity, Social network services, social networking (online), spatiotemporal patterns, Spatiotemporal phenomena, Urban areas, Yelp |
| Abstract | Given that the USA and Germany are the most populous countries in North America and Western Europe, understanding the behavioral differences between American and German users of online social networks is essential. In this work, we conduct a data-driven study based on the Yelp Open Dataset. We demonstrate the behavioral characteristics of both American and German users from different aspects, i.e., social connectivity, review styles, and spatiotemporal patterns. In addition, we construct a classification model to accurately recognize American and German users according to the behavioral data. Our model achieves high classification performance with an F1-score of 0.891 and AUC of 0.949. |
| DOI | 10.26599/BDMA.2018.9020024 |
