Understanding the Behavioral Differences Between American and German Users: A Data-Driven Study
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 demon...
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Language: | English |
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Tsinghua University Press
2018-12-01
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Series: | Big Data Mining and Analytics |
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Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2018.9020024 |
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author | Chenxi Yang Yang Chen Qingyuan Gong Xinlei He Yu Xiao Yuhuan Huang Xiaoming Fu |
author_facet | Chenxi Yang Yang Chen Qingyuan Gong Xinlei He Yu Xiao Yuhuan Huang Xiaoming Fu |
author_sort | Chenxi Yang |
collection | DOAJ |
description | 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. |
format | Article |
id | doaj-art-a0aa95823e0a46e9ac7345c237972178 |
institution | Kabale University |
issn | 2096-0654 |
language | English |
publishDate | 2018-12-01 |
publisher | Tsinghua University Press |
record_format | Article |
series | Big Data Mining and Analytics |
spelling | doaj-art-a0aa95823e0a46e9ac7345c2379721782025-02-02T06:00:36ZengTsinghua University PressBig Data Mining and Analytics2096-06542018-12-011428429610.26599/BDMA.2018.9020024Understanding the Behavioral Differences Between American and German Users: A Data-Driven StudyChenxi Yang0Yang Chen1Qingyuan Gong2Xinlei He3Yu Xiao4Yuhuan Huang5Xiaoming Fu6<institution content-type="dept">School of Computer Science</institution>, <institution>Fudan University</institution>, <city>Shanghai</city> <postal-code>200433</postal-code>, <country>China</country>, and the <institution content-type="dept">Engineering Research Center of Cyber Security Auditing and Monitoring</institution>, <institution>Ministry of Education</institution>, <city>Shanghai </city><postal-code>200433</postal-code>, <country>China</country>.<institution content-type="dept">School of Computer Science</institution>, <institution>Fudan University</institution>, <city>Shanghai</city> <postal-code>200433</postal-code>, <country>China</country>, and the <institution content-type="dept">Engineering Research Center of Cyber Security Auditing and Monitoring</institution>, <institution>Ministry of Education</institution>, <city>Shanghai </city><postal-code>200433</postal-code>, <country>China</country>.<institution content-type="dept">School of Computer Science</institution>, <institution>Fudan University</institution>, <city>Shanghai</city> <postal-code>200433</postal-code>, <country>China</country>, and the <institution content-type="dept">Engineering Research Center of Cyber Security Auditing and Monitoring</institution>, <institution>Ministry of Education</institution>, <city>Shanghai </city><postal-code>200433</postal-code>, <country>China</country>.<institution content-type="dept">School of Computer Science</institution>, <institution>Fudan University</institution>, <city>Shanghai</city> <postal-code>200433</postal-code>, <country>China</country>, and the <institution content-type="dept">Engineering Research Center of Cyber Security Auditing and Monitoring</institution>, <institution>Ministry of Education</institution>, <city>Shanghai </city><postal-code>200433</postal-code>, <country>China</country>.<institution content-type="dept">Department of Communications and Networking</institution>, <institution>Aalto University</institution>, <postal-code>02150</postal-code> <city>Espoo</city>, <country>Finland</country>.<institution content-type="dept">Faculty of European Languages and Cultures</institution>, <institution>Guangdong University of Foreign Studies</institution>, <city>Guangzhou</city> <postal-code>510420</postal-code>, <country>China</country>.<institution content-type="dept">Institute of Computer Science</institution>, <institution>University of Göttingen</institution>, <postal-code>37077</postal-code> <city>Göttingen</city>, <country>Germany</country>.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.https://www.sciopen.com/article/10.26599/BDMA.2018.9020024behavioral differenceonline social networksyelpmachine learning |
spellingShingle | Chenxi Yang Yang Chen Qingyuan Gong Xinlei He Yu Xiao Yuhuan Huang Xiaoming Fu Understanding the Behavioral Differences Between American and German Users: A Data-Driven Study Big Data Mining and Analytics behavioral difference online social networks yelp machine learning |
title | Understanding the Behavioral Differences Between American and German Users: A Data-Driven Study |
title_full | Understanding the Behavioral Differences Between American and German Users: A Data-Driven Study |
title_fullStr | Understanding the Behavioral Differences Between American and German Users: A Data-Driven Study |
title_full_unstemmed | Understanding the Behavioral Differences Between American and German Users: A Data-Driven Study |
title_short | Understanding the Behavioral Differences Between American and German Users: A Data-Driven Study |
title_sort | understanding the behavioral differences between american and german users a data driven study |
topic | behavioral difference online social networks yelp machine learning |
url | https://www.sciopen.com/article/10.26599/BDMA.2018.9020024 |
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