Journal cover Journal topic
Advances in Science and Research The open-access proceedings of the European Meteorological Society (EMS)

Journal metrics

  • h5-index value: 12 h5-index 12
Adv. Sci. Res., 14, 217-226, 2017
https://doi.org/10.5194/asr-14-217-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
11 Jul 2017
Public crowdsensing of heat waves by social media data
Valentina Grasso1,2, Alfonso Crisci1, Marco Morabito1, Paolo Nesi3, and Gianni Pantaleo3 1Institute of Biometeorology, Italian National Research Council, Via G. Caproni 8, Florence, Italy
2LaMMA Consortium, Via Madonna del Piano 10, Sesto Fiorentino (FI), Italy
3DISIT Lab, Distributed Systems and internet/Data Intelligence and Technologies Lab, Dep. of Information Engineering (DINFO), University of Florence, Italy Via S. Marta, Florence, Italy
Abstract. Investigating on society-related heat wave hazards is a global issue concerning the people health. In the last two decades, Europe experienced several severe heat wave episodes with catastrophic effects in term of human mortality (2003, 2010 and 2015). Recent climate investigations confirm that this threat will represent a key issue for the resiliency of urban communities in next decades. Several important mitigation actions (Heat-Health Action Plans) against heat hazards have been already implemented in some WHO (World Health Organization) European region member states to encourage preparedness and response to extreme heat events. Nowadays, social media (SM) offer new opportunities to indirectly measure the impact of heat waves on society. Using the crowdsensing concept, a micro-blogging platform like Twitter may be used as a distributed network of mobile sensors that react to external events by exchanging messages (tweets). This work presents a preliminary analysis of tweets related to heat waves that occurred in Italy in summer 2015. Using TwitterVigilance dashboard, developed by the University of Florence, a sample of tweets related to heat conditions was retrieved, stored and analyzed for main features. Significant associations between the daily increase in tweets and extreme temperatures were presented. The daily volume of Twitter users and messages revealed to be a valuable indicator of heat wave impact at the local level, in urban areas. Furthermore, with the help of Generalized Additive Model (GAM), the volume of tweets in certain locations has been used to estimate thresholds of local discomfort conditions. These city-specific thresholds are the result of dissimilar climatic conditions and risk cultures.

Citation: Grasso, V., Crisci, A., Morabito, M., Nesi, P., and Pantaleo, G.: Public crowdsensing of heat waves by social media data, Adv. Sci. Res., 14, 217-226, https://doi.org/10.5194/asr-14-217-2017, 2017.
Publications Copernicus
Download
Short summary
This work presents an analysis of tweets related to heat waves occurred in Italy in summer 2015. Social media offer new opportunities to indirectly measure the impact of heat waves on society. Tweets related to heat conditions were retrieved and analysed for main features. The daily volume of users and messages was a valuable indicator of heat wave impact in urban areas. The volume of tweets in certain locations was used to estimate thresholds of local discomfort conditions.
This work presents an analysis of tweets related to heat waves occurred in Italy in summer 2015....
Share