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Spatiotemporal Analysis on Sentiments and Retweet Patterns of Tweets for Disasters

  • Sijing Chen
  • Jin MaoEmail author
  • Gang Li
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11420)

Abstract

Twitter provides an important channel for public to share feelings, attitudes and concerns about disasters. In this study, we aim to explore how spatiotemporal factors affect people’s sentiment in disaster situations and how the area type, time stage and sentiment of the tweets affect the extent and speed of tweets’ diffusion. After analyzing 531,912 geo-tagged tweets about Hurricane Harvey, we found that on-site tweets are more positive than off-site tweets across the time; neutral tweets spread broader and faster than tweets with sentiment propensity; on-site tweets and tweets posted at early stages tend to be more popular. These findings could enable authorities and response organizations to better comprehend people’s feelings and behaviors in social media and their changes over time and space. In future, we will analyze the influence of the interactions among sentiment, location and time to retweet patterns.

Keywords

Disaster Sentiment analysis Retweet pattern 

Notes

Acknowledgements

The paper is supported by the National Natural Science Foundation of China (No. 71790612, No. 71804135 and No. 71603189).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Wuhan UniversityWuhanChina

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