Estimating and Visualizing the Time-varying Effects of a Binary Covariate on Longitudinal Big Text Data

DOI

10.2991/ijndc.2017.5.4.6How to use a DOI?

Keywords

Text mining, Summarization, Semiparametric modeling, Classification, Animation, Knowledge discovery.

Abstract

We propose a method to estimate and visualize effects of a binary covariate on the longitudinally observed text data. Our method consists of series of analytical methods: extracting keywords through a morphological analysis, estimating the time-varying regression coefficient of a binary covariate for keyword's appearance and frequency, classifying summary of estimates, and visualizing the time-varying effects of a binary covariate in animated scatter plots. The procedure is demonstrated with Peace Declaration text data observed for forty years in two cities.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Shizue Izumi
AU  - Tetsuji Tonda
AU  - Noriyuki Kawano
AU  - Kenichi Satoh
PY  - 2017
DA  - 2017/10/02
TI  - Estimating and Visualizing the Time-varying Effects of a Binary Covariate on Longitudinal Big Text Data
JO  - International Journal of Networked and Distributed Computing
SP  - 243
EP  - 253
VL  - 5
IS  - 4
SN  - 2211-7946
UR  - https://doi.org/10.2991/ijndc.2017.5.4.6
DO  - 10.2991/ijndc.2017.5.4.6
ID  - Izumi2017
ER  -