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Regional Analysis Based on Location Information and Time Series Change Using Geotagged Tweets

Authors:
Masaki Endo
Shigeyoshi Ohno
Masaharu Hirota
Tetsuya Araki
Hiroshi Ishikawa

Keywords: location information; time series; Twitter.

Abstract:
Because of the popularization of Social Networking Services (SNSs), it is possible to acquire large amounts of data in real time. For this reason, various studies are being conducted to analyze social media data and to extract real-world events. Among them, a salient advantage of analysis using positional information is that one can accurately extract events from target areas of interest. However, data having position information in social media data remain few: the data amount might be insufficient for analysis. Therefore, we are assessing a method for real-time analysis using data with location information that has been accumulated over a certain period of time. In this research, we are studying a method of regional analysis by position information and time series change using tweets with Twitter position information. Herein, we explain the results obtained from area analysis using the proposed method.

Pages: 1 to 6

Copyright: Copyright (c) IARIA, 2019

Publication date: March 24, 2019

Published in: conference

ISSN: 2308-4448

ISBN: 978-1-61208-697-2

Location: Valencia, Spain

Dates: from March 24, 2019 to March 28, 2019