Social Benefit Evaluation of Transportation Policy Based on Social Media

DOI

10.2991/ammsa-17.2017.56How to use a DOI?

Keywords

intelligent transportation; parameter calibration; fuzzy clustering; social media; data mining; transportation policy component

Abstract

Social Media data can truly reflect hot spot and attitude of people to transport policy. The scientific social media data mining and processing method can excavate effectively the public's focus to transportation policy and provide a new transportation policy evaluation way. Firstly, the evaluation index system of transportation policy including its social benefit is established. Secondly, a Social Media Chinese text data mining scheme is presented, using Python and the information processing technology of Chinese synonym, fuzzy clustering weight of text data based on fuzzy clustering method. Then a social benefit evaluation index calibration method of transportation policy is presented. Finally, social benefit of Beijing public transportation pricing policy is evaluated, the public's attention is transport comfort.

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  - CONF
AU  - Xin Wang
AU  - Xingqiang Zhang
AU  - Yonggang Song
AU  - Shan Zhu
AU  - Xueyuan Wang
PY  - 2017/05
DA  - 2017/05
TI  - Social Benefit Evaluation of Transportation Policy Based on Social Media
BT  - Proceedings of the 2017 International Conference on Applied Mathematics, Modelling and Statistics Application (AMMSA 2017)
PB  - Atlantis Press
SP  - 252
EP  - 255
SN  - 1951-6851
UR  - https://doi.org/10.2991/ammsa-17.2017.56
DO  - 10.2991/ammsa-17.2017.56
ID  - Wang2017/05
ER  -