@I to @Me：An Anatomy of Twitter上不断变化的行为
@I to @Me: An Anatomy of Username Changing Behavior on Twitter
摘要：
在线社交网络（OSN）上的用户的身份由她的简档、内容和网络属性定义。OSN允许用户随时间改变他们的在线属性，以反映他们现实生活中的变化。用户内容和网络属性的时间变化在文献中已经得到了很好的研究，但很少有研究探讨了在线用户的配置文件属性的时间变化。这项工作使第一次尝试研究改变一个独特的配置文件属性的用户-用户名和流行的OSN，允许用户多次更改用户名- Twitter。我们在宏观层面上收集、监测和分析了870万Twitter用户，在微观层面上收集了1万用户，以了解用户名更改行为。我们发现，大约10%的受监控Twitter用户选择更改用户名，可能的原因包括空间增益，追随者增益和用户名推广。很少有用户会切换回他们过去的用户名，但是他们更喜欢切换回最近丢弃的用户名。更改用户名的用户比不更改用户名的用户更活跃，更受欢迎。用户的入度、活跃度和创建年份与用户名更改频率之间的相关性较弱。我们相信，用户过去的用户名以及从过去推断出的相关好处，可以帮助Twitter向用户建议一组合适的用户名。过去的用户名也可以在其他应用程序中提供帮助，例如搜索和链接用户的多个OSN帐户以及将多个Twitter配置文件与单个用户关联。
英文摘要：
An identity of a user on an online social network (OSN) is defined by her profile, content and network attributes. OSNs allow users to change their online attributes with time, to reflect changes in their real-life. Temporal changes in users' content and network attributes have been well studied in literature, however little research has explored temporal changes in profile attributes of online users. This work makes the first attempt to study changes to a unique profile attribute of a user - username and on a popular OSN which allows users to change usernames multiple times - Twitter. We collect, monitor and analyze 8.7 million Twitter users at macroscopic level and 10,000 users at microscopic level to understand username changing behavior. We find that around 10% of monitored Twitter users opt to change usernames for possible reasons such as space gain, followers gain, and username promotion. Few users switch back to any of their past usernames, however prefer recently dropped usernames to switch back to. Users who change usernames are more active and popular than users who don't. In-degree, activity and account creation year of users are weakly correlated with their frequency of username change. We believe that past usernames of a user and their associated benefits inferred from the past, can help Twitter to suggest its users a set of suitable usernames to change to. Past usernames may also help in other applications such as searching and linking multiple OSN accounts of a user and correlating multiple Twitter profiles to a single user.
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。
