論文

査読有り 本文へのリンクあり
2020年1月

ソーシャルグラフによる居住地推定のためのユーザプロフィール分析

人工知能学会論文誌
  • 廣中詩織
  • ,
  • 吉田光男
  • ,
  • 梅村恭司

35
1
開始ページ
E-J71_1
終了ページ
10
記述言語
日本語
掲載種別
研究論文(学術雑誌)
DOI
10.1527/tjsai.E-J71

Users’ attributes, such as home location, are necessary for various applications, such as news recommendations and event detections. However, most real user attributes (e.g., home location) are not open to the public. Therefore, their attributes are estimated by relationships between users. A social graph constructed from relationships between users can help estimate home locations, but it is difficult to collect many relationships, such as followers’ relationships. We focus on users whose home locations are difficult to estimate, so that we can select users whose locations can be accurately estimated before collecting relationships. In this paper, we use their profiles which can be collected before collecting relationships. Then, we analyze difficult users with their profiles. As a result, we found that users whose home locations incorrectly estimated had a longer duration since the date their account was created, longer name, and longer description. In addition, the results indicated that the users whose home locations were incorrectly estimated differed from those whose home locations could not be estimated.

リンク情報
DOI
https://doi.org/10.1527/tjsai.E-J71 本文へのリンクあり
ID情報
  • DOI : 10.1527/tjsai.E-J71

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