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Tweets from Justin Bieber's Heart: The Dynamics of the 'Location' Field in User Profiles

机译:贾斯汀·比伯(Justin Bieber)心中的推文:用户个人资料中“位置”字段的动态

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Little research exists on one of the most common, oldest, and most utilized forms of online social geographic information: the "location" field found in most virtual community user profiles. We performed the first in-depth study of user behavior with regard to the location field in Twitter user profiles. We found that 34% of users did not provide real location information, frequently incorporating fake locations or sarcastic comments that can fool traditional geographic information tools. When users did input their location, they almost never specified it at a scale any more detailed than their city. In order to determine whether or not natural user behaviors have a real effect on the "locatability" of users, we performed a simple machine learning experiment to determine whether we can identify a user's location by only looking at what that user tweets. We found that a user's country and state can in fact be determined easily with decent accuracy, indicating that users implicitly reveal location information, with or without realizing it. Implications for location-based services and privacy are discussed.
机译:关于在线社会地理信息的最常见,最古老和使用最多的形式之一的研究很少:大多数虚拟社区用户个人资料中的“位置”字段。我们对Twitter用户个人资料中的位置字段进行了用户行为的首次深入研究。我们发现34%的用户没有提供真实的位置信息,经常包含虚假的位置或讽刺性评论,这些信息可能使传统的地理信息工具蒙蔽。用户输入位置时,几乎从未指定过比其城市更详细的比例。为了确定自然用户行为是否对用户的“可定位性”产生了实际影响,我们执行了一个简单的机器学习实验,以确定是否可以仅通过查看用户的推文来识别用户的位置。我们发现,实际上可以轻松地以适当的准确性确定用户的国家和州,这表明用户隐含地揭示了位置信息,无论是否意识到。讨论了基于位置的服务和隐私的含义。

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