Abstract

Microblogging systems such as Twitter have seen explosive use in public and private sectors. The age information of microbloggers can be very useful for many applications such as viral marketing and social studies/surveys. Current microblogging systems, however, have very sparse age information. In this paper, we present MAIF, a novel framework that explores public content and interaction information in microblogging systems to explore the hidden ages of microbloggers. We thoroughly evaluate the accuracy of MAIF with a real-world dataset with 54, 879 Twitter users. Our results show that MAIF can achieve up to 81.38% inference accuracy and outperforms the state of the art by 9.15%. We also discuss some countermeasures to alleviate the possible privacy concerns caused by MAIF.

Original languageEnglish (US)
Title of host publicationProceedings of the 10th International Conference on Web and Social Media, ICWSM 2016
PublisherAAAI Press
Pages476-485
Number of pages10
ISBN (Electronic)9781577357582
StatePublished - 2016
Event10th International Conference on Web and Social Media, ICWSM 2016 - Cologne, Germany
Duration: May 17 2016May 20 2016

Other

Other10th International Conference on Web and Social Media, ICWSM 2016
CountryGermany
CityCologne
Period5/17/165/20/16

ASJC Scopus subject areas

  • Computer Networks and Communications

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  • Cite this

    Zhang, J., Hu, X., Zhang, Y., & Liu, H. (2016). Your age is no secret: Inferring microbloggers' ages via content and interaction analysis. In Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016 (pp. 476-485). AAAI Press.