Location2Vec: Generating Distributed Representation of Location by Using Geo-tagged Microblog Posts

  • Yoshiyuki ShojiEmail author
  • Katsurou Takahashi
  • Martin J. Dürst
  • Yusuke Yamamoto
  • Hiroaki Ohshima
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11186)


This paper proposes a method to represent the characteristics of a place (i.e., use of the venue, atmosphere of the area) by using geo-tagged microblog posts around the place. It enables a vector representation of a location similar to the distributed representation of a term in Word2Vec. Our method uses a simple neural network that is trained through the task of estimating the terms that appear in tweets posted from the area. The effectiveness of our method is illustrated through an experiment of a comparison of similar locations in Tokyo and Kyoto.


Geo-tag Social sensing Word2Vec Social media analysis 



This work was supported by JSPS KAKENHI Grant Numbers JP18K18161, JP17K17832, JP18KT0097, JP16H02906, JP16H01756, JP17H00762, JP18H03243.


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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Aoyama Gakuin UniversitySagamihara-shiJapan
  2. 2.University of HyogoKobe-shiJapan
  3. 3.Shizuoka UniversityHamamatsu-shiJapan

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