Abstract
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.
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Acknowledgements
This work was supported by JSPS KAKENHI Grant Numbers JP18K18161, JP17K17832, JP18KT0097, JP16H02906, JP16H01756, JP17H00762, JP18H03243.
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Shoji, Y., Takahashi, K., Dürst, M.J., Yamamoto, Y., Ohshima, H. (2018). Location2Vec: Generating Distributed Representation of Location by Using Geo-tagged Microblog Posts. In: Staab, S., Koltsova, O., Ignatov, D. (eds) Social Informatics. SocInfo 2018. Lecture Notes in Computer Science(), vol 11186. Springer, Cham. https://doi.org/10.1007/978-3-030-01159-8_25
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