Abstract
Geotagging is the process of labeling data and information with geographical identification metadata, and text mining refers to the process of deriving information from text through data analytics. Geotagging and text mining are used to mine rich sources of social media data, such as video, website, text, and Quick Response (QR) code. They have been frequently used to model consumer behaviors and market trends. This study uses both techniques to understand the resilience of infrastructure in Chennai, India using data mined from the 2015 flood. This paper presents a conceptual study on the potential use of social media (Twitter in this case) to better understand infrastructure resiliency. Using feature-extraction techniques, the research team extracted Twitter data from tweets generated by the Chennai population during the flood. First, this study shows that these techniques are useful in identifying locations, defects, and failure intensities of infrastructure using the location metadata from geotags, words containing the locations, and the frequencies of tweets from each location. However, more efforts are needed to better utilize the texts generated from the tweets, including a better understanding of the cultural contexts of the words used in the tweets, the contexts of the words used to describe the incidents, and the least frequently used words.
Department(s)
Technology and Construction Management
Document Type
Article
DOI
https://doi.org/10.1016/j.eng.2018.03.010
Rights Information
© 2018 The authors. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords
Engineering design, Flooding, Social media
Publication Date
4-1-2018
Recommended Citation
Chong, Wai K., Hariharan Naganathan, Huan Liu, Samuel Ariaratnam, and Joonhoon Kim. "Understanding infrastructure resiliency in Chennai, India using Twitter’s Geotags and texts: a preliminary study." Engineering 4, no. 2 (2018): 218-223.
Journal Title
Engineering