With the increasing popularity of mobile devices and the wide adoption of mobile Apps,an increasing concern of privacy issues is raised.Privacy policy is identified as a proper medium to indicate the legal terms,such ...With the increasing popularity of mobile devices and the wide adoption of mobile Apps,an increasing concern of privacy issues is raised.Privacy policy is identified as a proper medium to indicate the legal terms,such as the general data protection regulation(GDPR),and to bind legal agreement between service providers and users.However,privacy policies are usually long and vague for end users to read and understand.It is thus important to be able to automatically analyze the document structures of privacy policies to assist user understanding.In this work we create a manually labelled corpus containing 231 privacy policies(of more than 566,000 words and 7,748 annotated paragraphs).We benchmark our data corpus with 3 document classification models and achieve more than 82%on F1-score.展开更多
基金This work was supported by the National Natural Science Foundation of China(Grant Nos.61802275 and U1836214)the Innovation fund of Tianjin University(2020XRG-0022).
文摘With the increasing popularity of mobile devices and the wide adoption of mobile Apps,an increasing concern of privacy issues is raised.Privacy policy is identified as a proper medium to indicate the legal terms,such as the general data protection regulation(GDPR),and to bind legal agreement between service providers and users.However,privacy policies are usually long and vague for end users to read and understand.It is thus important to be able to automatically analyze the document structures of privacy policies to assist user understanding.In this work we create a manually labelled corpus containing 231 privacy policies(of more than 566,000 words and 7,748 annotated paragraphs).We benchmark our data corpus with 3 document classification models and achieve more than 82%on F1-score.
