数字文体学：跨社交网络链接个人资料
Digital Stylometry: Linking Profiles Across Social Networks
摘要：
越来越多的用户在多个社交媒体和社交网站上拥有账户。因此，对跨不同社交网络匹配用户账户和简档以便创建用户的聚合简档的兴趣日益增加。在本文中，我们提出了数字Stylometry，这是一种匹配用户通过风格启发技术的模型。我们使用标准和新颖的技术，尝试了语言、时间和时间-语言组合模型来匹配用户帐户。使用公开的数据，我们的最佳模型，一个结合时间语言的模型，能够正确匹配Twitter和Facebook上5,612个不同用户中31%的账户。
英文摘要：
There is an ever growing number of users with accounts on multiple social media and networking sites. Consequently, there is increasing interest in matching user accounts and profiles across different social networks in order to create aggregate profiles of users. In this paper, we present models for Digital Stylometry, which is a method for matching users through stylometry inspired techniques. We experimented with linguistic, temporal, and combined temporal-linguistic models for matching user accounts, using standard and novel techniques. Using publicly available data, our best model, a combined temporal-linguistic one, was able to correctly match the accounts of 31% of 5,612 distinct users across Twitter and Facebook.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
