Influenza surveillance through social media data is becoming an important research topic because it could enhance the capabilities of official surveillance systems in monitoring the outbreak of seasonal flu, by providing healthcare organization with improved situational awareness. In this paper, the two influenza seasons 2016- 2017 and 2017-2018, restricted to Italy, are investigated by analyzing the tweets posted by users regarding influenza-like illness. Two types of analysis are performed. The first studies the correlation between the tweets containing the most frequent flu related words with the data provided by the Italian Inf luNet surveillance system. The second one examines the sentiment of people on the medicines used to heal flu. We show that there is a strict correlation between the reports published on the Inf luNet system, and the contents posted by Twitter users about their symptoms and health state. Moreover, we found that the sentiment expressed by people regarding the treatment, in terms of medicines, taken to heal seems rather negative.
Twitter-based Influenza Surveillance: An Analysis of the 2016-2017 and 2017-2018 Seasons in Italy
Carmela Comito;Agostino Forestiero;Clara Pizzuti
2018
Abstract
Influenza surveillance through social media data is becoming an important research topic because it could enhance the capabilities of official surveillance systems in monitoring the outbreak of seasonal flu, by providing healthcare organization with improved situational awareness. In this paper, the two influenza seasons 2016- 2017 and 2017-2018, restricted to Italy, are investigated by analyzing the tweets posted by users regarding influenza-like illness. Two types of analysis are performed. The first studies the correlation between the tweets containing the most frequent flu related words with the data provided by the Italian Inf luNet surveillance system. The second one examines the sentiment of people on the medicines used to heal flu. We show that there is a strict correlation between the reports published on the Inf luNet system, and the contents posted by Twitter users about their symptoms and health state. Moreover, we found that the sentiment expressed by people regarding the treatment, in terms of medicines, taken to heal seems rather negative.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


