Predicting various types of user attributes in Twitter by using personalized pagerank

Kazuya Uesato, Hiroki Asai, Hayato Yamana

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Predicting various types of user-attributes in social networks has become indispensable for personalizing applications since there are many non-disclosed attributes in social networks. However, extracted attributes in existing works are limited to pre-defined types of attributes, which results in no extraction of unexpected-types of attributes. In this paper, we therefore propose a novel method that extracts various, i.e., unlimited, types of attributes by adopting personalized PageRank to a large social network. The experimental results using over 7.9 million of Japanese Twitter-users show that our proposed method successfully extracts four types of attributes per-user in average with 0.841 of MAP@20.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015
EditorsFeng Luo, Kemafor Ogan, Mohammed J. Zaki, Laura Haas, Beng Chin Ooi, Vipin Kumar, Sudarsan Rachuri, Saumyadipta Pyne, Howard Ho, Xiaohua Hu, Shipeng Yu, Morris Hui-I Hsiao, Jian Li
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2825-2827
Number of pages3
ISBN (Electronic)9781479999255
DOIs
Publication statusPublished - 2015 Dec 22
Event3rd IEEE International Conference on Big Data, IEEE Big Data 2015 - Santa Clara, United States
Duration: 2015 Oct 292015 Nov 1

Publication series

NameProceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015

Other

Other3rd IEEE International Conference on Big Data, IEEE Big Data 2015
CountryUnited States
CitySanta Clara
Period15/10/2915/11/1

Keywords

  • Twitter
  • personalized PageRank
  • social networking service
  • user attribute prediction
  • user profiling

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Software

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