Tweeting after an earthquake: user localization and communication patterns during the 2012 Emilia seismic sequence

Federica Magnoni Federica Magnoni,Lorenza Parisi Lorenza Parisi,Francesca Comunello Francesca Comunello,Emanuele Casarotti Emanuele Casarotti,Valentino Lauciani Valentino Lauciani

doi:10.4401/ag-6945

Abstract

The main goal of this paper is analysing how user’s location, relative to the epicenter of an earthquake, affects the different tweeting strategies adopted. For this purpose, we analyze a dataset of tweets that were generated around the 2012 Emilia earthquakes and that are geolocalized in Italy. In our analysis, we rely on existing literature on social media and natural disasters, considering literature exploring interactions and influence on Twitter, and literature focusing on the role of geolocalized user-generated information in disaster response.

Highlights

Literature on disaster research [Rodriguez et al 2007], and on emergency and crisis communication [Coombs and Holladay 2010], has a long and established tradition, while research on the role of social media during disasters has been defined as “a largely untapped site of study” [Potts 2013, p. 98]
In recent years have social media scholars started devoting their attention to the role of social network sites (SNS) during natural disasters, analysing different contexts and social media platforms, and adopting both a top-down perspective, focusing on institutional communication and emergency management processes [Hughes et al 2014a, Giacobe and Soule 2014], or on the role of nonprofit and media organizations [Mularidharan et al 2011]; and a bottom-up perspective
Focusing on social media adoption by local level emergency managers in the USA, Plotnick et al [2015] identify the main barriers to social media usage for sending out and gathering information, which include the lack of staff, the lack of formal social media policies, the lack of staff and experience with social media, the trustworthiness of public generated content, underlining that countylevel agencies “are not yet ready to embrace SM and use it to its fullest potential” [p. 10]

Summary

TWEETING AFTER AN EARTHQUAKE

The 2012 seismic sequence in Emilia is one of the first natural disasters in Italy that has been largely commented on Twitter, and #terremoto (“earthquake” in Italian) has been a long-lasting Italian trending topic on the platform. While the majority of tweets in our database is produced shortly after a major shake, when considering tweet distribution within a single zone (Figure 6), other differences emerge. During the whole seismic sequence it published 909 geolocalized tweets, both in the red and in the white zone (such tweets are related to the Emilia sequence, but report every earthquake stronger than 2.0 occurring in Italy). UTC, 47 minutes after the first shake, and it officially reports a ML 5.9 earthquake localized in Modena Province Analyzing their profiles and the number of followers, following and tweets they have produced, the most active users in the 3 zones, with the exception of @INGVterremoti, tend to be “common” users. Number of users Users producing only 1 tweet Tweets by most active userb % of tweets by 4 most active users Average Number of tweets by user

Mentions and RT

Emotive Effect description Routine interruption Second hand information

Findings

Meta social media Other