Understanding the Behavioural Differences Between American and German Users: A Data-driven Study

Chenxi Yang; Yang Chen; Qingyuan Gong; Xinlei He; Yu Xiao; Yuhuan Huang; Xiaoming Fu

doi:10.26599/BDMA.2018.9020024

Understanding the Behavioural Differences Between American and German Users: A Data-driven Study

Chenxi Yang, Yang Chen, Qingyuan Gong, Xinlei He, Yu Xiao, Yuhuan Huang, Xiaoming Fu

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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.

Original language	English
Pages (from-to)	284 - 296
Number of pages	13
Journal	Big Data Mining and Analytics
Volume	1
Issue number	4
DOIs	https://doi.org/10.26599/BDMA.2018.9020024
Publication status	Published - 2 Jul 2018
MoE publication type	A1 Journal article-refereed

Keywords

Behavioral Difference
online social network
Yelp
Machine learning

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10.26599/BDMA.2018.9020024

ELEC-Yang-et-al-Understanding-the-behavioral-BDMaAFinal published version, 865 KB

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title = "Understanding the Behavioural Differences Between American and German Users: A Data-driven Study",

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.",

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AU - Yang, Chenxi

AU - Chen, Yang

AU - Gong, Qingyuan

AU - He, Xinlei

AU - Xiao, Yu

AU - Huang, Yuhuan

AU - Fu, Xiaoming

PY - 2018/7/2

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AB - 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.

KW - Behavioral Difference

KW - online social network

KW - Yelp

KW - Machine learning

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JF - Big Data Mining and Analytics

IS - 4

ER -

Understanding the Behavioural Differences Between American and German Users: A Data-driven Study

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Keywords

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