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L. Parisi, F. Comunello, A. Amico
2013 Sardinia floods.
Exploring conversations on Twitter
among citizens, institutions and Twitstars
Outline
• Social media and emergency communication during natural
disasters
• The Italian context
• Sardinian floods 2013: #allertameteoSAR
• Aims and methodology
• Findings:
the evolution of a crowdsourced emergency management
the role of Twistars and the role of institutions
• Digital volunteers and civic engagement
Social media and natural disasters
Social media have served as powerful tools for emergency management
and disaster relief in many recent emergency situations worldwide.
Twitter is a suitable platform for information spread during natural
disasters: prevalence of public accounts; large amount of disaster-related
conversations during and after ‘acute events’; RT (retweet) feature
(information spread), ‘public’ dimension of #hashtag conversations.
Research on the role social media during natural disasters has been
oriented towards both practical work (e.g. White 2012) and pure scholarly
research. While such approaches often need to be kept separated, for
analytical purposes, our understanding of the role of social media during
natural disasters would surely benefit from a stronger integration between
practical and theoretical work (e.g. Bruns et al., 2012; Mileti, Crowe, 2012).
Research on social media during natural disasters, moreover, can give us
rich insight on interaction dynamics on social media in broader terms
(influence, information spread, user engagement).
Background: research on social media and natural
disasters
Main topics: information spread, the role of so-called “influencers”,
citizens’ activity, the role of institutions, disaster-relief related practices,
digital volunteers (Starbid, Palen, 2011), memory and mourning
Methods: mainly quantitative; some scholars integrate quantitative and
qualitative methods.
As boyd and Crawford (2011) suggest, numbers do not “speak for
themselves”: if we do not want to limit our research to descriptive
statistics, there is a need for relevant research questions and for broader
theoretical frameworks in order to interpret big data usefully.
A broader theoretical framework: participatory cultures (Jenkins et al.
2009), new forms of civic engagement (Dahlgren, 2009; Bennet 2008), in
the context of networked individualism and sociability (Rainie and
Wellman, 2012).
The Italian context
Our presentation is a part of a broader research project on
social media and emergency communication in the Italian
context.
Italian public institutions don’t tribute high efforts in
communicating trough social media during “acute events”
i.e. Italian Civil Protection is not using any social media.
Moreover, even when institutions use social media accounts
in such contexts, they appear far less influential than other
social media users. Sometimes, they don’t appear fully aware
of the potential of social media (e.g.: Garfagnana earthquake
jan 2013: the Municipality of Castelnuovo tweeted to
evacuate the village, even if it was not necessary, nor agreed
with the Civil Protection or other institutions)
18 November 2013: heavy floods occurred in Sardinia
(450 mm in 12 hours, half than the annual average
rainfall), 16 people died
photo credit: m.todayonline.com
#allertameteoSAR
Few hours after the rainfall (12.46 pm) an Italian Twitstar (@insopportabile,
69.000 followers) created the hashtag #allertameteoSAR. The first tweet was:
“Grandi problemi per il maltempo in Sardegna. Segnalateli con il tag
#allertameteoSAR. Grazie” (“Big troubles because of bad weather in
Sardegna. Report them with the tag #allertameteoSAR. Thank you”)
Italian language uses several terms to describe floods: in the first hours,
several hashtags have been used: #Sardegna, #Olbia #Cagliari (locations);
#SOSalluvionesardegna, #alluvione, #forzasardegna
As institutional social media communication was generally lacking, the
hashtag #allertameteoSAR witnessed a user-driven shift
Ecological approach: AllertameteoSAR digital volunteers carried out several
communication activities during Sardinian floods making use of different online
tools: Twitter, Facebook, collaborative OS maps, Google docs, etc.
Our Research Goals
How users managed the diffusion of the #allertameteoSAR?
How did they succeed in creating an hashtag that has been
adopted only to share practical information (no expression of
solidarity, no general comments)?
- give a quantitative account of Twitter activity;
- analyze information spread and patterns of influence;
- explore the interactions between citizen-generated content,
institutional communication, information by media outlets and
by celebrities
Methods
We analyzed the whole dataset of the tweets with hashtag
#allertameteoSAR that have been produced during the first week
of the Sardinian floods (18-24/11/2013): around 93.091 tweets
have been extracted through GNIP “Historical Power Track”.
Our research integrates quantitative and qualitative methods.
The quantitative side includes automated data analysis and
activity metrics; content analysis. Such quantitative methods are
integrated with a qualitative tweet analysis (close reading)
Findings #1
Tweet volume over time: 81,8% of the tweets during the first two days
of the floods
The hashtag
became #TT
Findings #2 Mapping the evolution of
crowdsourced emergency management practices
How to turn a “generic” Twitter hashtag conversation into a more practical -
disaster-recovery oriented – conversation
At the beginning the hashtag was used as a general-purpose hashtag;
afterwards, some active Twitter users succeeded in transforming it into the
“(un)official” hashtag for disaster recovery-related conversations.
3 phases:
1) from 12 pm 18/11: hashtag promotion and diffusion; several tweets
saying “please report the troubles (dangers, closed streets, etc.) using the
hashtag #allertameteoSAR”
2) from 23 pm 18/11: hashtag ‘cleaning’ and moderation; “no compassionate
RT please. It’s time to use the web for information”; “#allertameteoSAR is a channel for
URGENT information, not for thoughts. Use #forzasardegna or other hash for useless
things”
3) 19/11: hashtag is used to promote a multichannel logic for disaster
relief; “please put such information in the map. Otherwise we loose them and they
become useless”
Findings #3 Users, mentions and RT
Unique users: 25.421 (14.545 produced only 1 tweet with
#allertameteoSAR)
URL: 36,5% of the tweets
RT: 84% of the tweets (Bruns and Stieglitz 2014: during natural disasters
RT are 55 -70% of the whole tweets)
Most mentioned accounts belong to twitstars, popstars and local users
Some media and very few institutional accounts are mentioned
The most retweeted tweets (N=93, 100 RT or more) represent 15% of
the whole db.
The majority of those tweets communicate useful information (i.e.
emergency numbers; information about recovery centers; request for
specific resources, how to create a wi-fi public network etc.)
Findings #4 The role of Twistars
While a major role in promoting #allertameteoSAR has been played
by local “twitstars”, celebrity accounts (well-known Italian pop-stars)
appear as the most influential, having received the highest number of
mentions and retweets.
The 3 most retweeted tweets have been created by 3 Italian pop-stars
Marco Mengoni’s tweet
has been retweeted
1255 times
Most RT users over time (18-20 nov 2013)
0
50
100
150
200
250
300
350
400
11 12 13 14 15 16 17 18 19 20 21 22 23 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
18/11/2013 19/11/2013 20/11/2013
insopportabile
Virus1979C
Somma di
mengonimarco
Comune_Cagliari
ugocappellacci
Findings #6 The role of public institutions
The Municipality of Cagliari joined the conversation at 15.56 pm (18/11)
Ugo Cappellacci (former President of the Regional Government) joined at
1 am (19/11). Both accounts have been “invited” by the users (through
several mentions) to use #allertameteoSAR
Italian institutions appear far less influential than “twitstars” or
common social media users
Twitter users pointed out that Italian institutions were not playing an
active role in managing the emergency using social media. The Head of
the Italian Civil Protection reacted by minimizing the role of social media
and of the digital volunteers
Twitter users invited broadcast media (newspapers, tv shows) to cover the
event, stressing the distance between Twitter and the mass media agenda
Conclusions: digital volunteers and civic
engagement
During Sardinian floods #allertameteoSAR hashtag has been used to share
practical information and to coordinate disaster relief activities
Digital volunteers adopted an ecological approach sharing information among
several online platforms (Twitter, Facebook, collaborative OS maps, Google doc)
#allertameteoSAR hashtag is an example of emergent participatory culture
where civic engagement and digital volunteering coexist
Citizens as social sensors: user generated contents published on social media
produce risks and opportunities
Our next step: how can Institutions use such information to
effectively communicate during natural disasters?
Thank you!
lorenza.parisi@uniroma1.it @lorenzaparisi
francesca.comunello@uniroma1.it @fcomun

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#AllermatemeoSAR: social media and emergency communication

  • 1. L. Parisi, F. Comunello, A. Amico 2013 Sardinia floods. Exploring conversations on Twitter among citizens, institutions and Twitstars
  • 2. Outline • Social media and emergency communication during natural disasters • The Italian context • Sardinian floods 2013: #allertameteoSAR • Aims and methodology • Findings: the evolution of a crowdsourced emergency management the role of Twistars and the role of institutions • Digital volunteers and civic engagement
  • 3. Social media and natural disasters Social media have served as powerful tools for emergency management and disaster relief in many recent emergency situations worldwide. Twitter is a suitable platform for information spread during natural disasters: prevalence of public accounts; large amount of disaster-related conversations during and after ‘acute events’; RT (retweet) feature (information spread), ‘public’ dimension of #hashtag conversations. Research on the role social media during natural disasters has been oriented towards both practical work (e.g. White 2012) and pure scholarly research. While such approaches often need to be kept separated, for analytical purposes, our understanding of the role of social media during natural disasters would surely benefit from a stronger integration between practical and theoretical work (e.g. Bruns et al., 2012; Mileti, Crowe, 2012). Research on social media during natural disasters, moreover, can give us rich insight on interaction dynamics on social media in broader terms (influence, information spread, user engagement).
  • 4. Background: research on social media and natural disasters Main topics: information spread, the role of so-called “influencers”, citizens’ activity, the role of institutions, disaster-relief related practices, digital volunteers (Starbid, Palen, 2011), memory and mourning Methods: mainly quantitative; some scholars integrate quantitative and qualitative methods. As boyd and Crawford (2011) suggest, numbers do not “speak for themselves”: if we do not want to limit our research to descriptive statistics, there is a need for relevant research questions and for broader theoretical frameworks in order to interpret big data usefully. A broader theoretical framework: participatory cultures (Jenkins et al. 2009), new forms of civic engagement (Dahlgren, 2009; Bennet 2008), in the context of networked individualism and sociability (Rainie and Wellman, 2012).
  • 5. The Italian context Our presentation is a part of a broader research project on social media and emergency communication in the Italian context. Italian public institutions don’t tribute high efforts in communicating trough social media during “acute events” i.e. Italian Civil Protection is not using any social media. Moreover, even when institutions use social media accounts in such contexts, they appear far less influential than other social media users. Sometimes, they don’t appear fully aware of the potential of social media (e.g.: Garfagnana earthquake jan 2013: the Municipality of Castelnuovo tweeted to evacuate the village, even if it was not necessary, nor agreed with the Civil Protection or other institutions)
  • 6. 18 November 2013: heavy floods occurred in Sardinia (450 mm in 12 hours, half than the annual average rainfall), 16 people died photo credit: m.todayonline.com
  • 7. #allertameteoSAR Few hours after the rainfall (12.46 pm) an Italian Twitstar (@insopportabile, 69.000 followers) created the hashtag #allertameteoSAR. The first tweet was: “Grandi problemi per il maltempo in Sardegna. Segnalateli con il tag #allertameteoSAR. Grazie” (“Big troubles because of bad weather in Sardegna. Report them with the tag #allertameteoSAR. Thank you”) Italian language uses several terms to describe floods: in the first hours, several hashtags have been used: #Sardegna, #Olbia #Cagliari (locations); #SOSalluvionesardegna, #alluvione, #forzasardegna As institutional social media communication was generally lacking, the hashtag #allertameteoSAR witnessed a user-driven shift Ecological approach: AllertameteoSAR digital volunteers carried out several communication activities during Sardinian floods making use of different online tools: Twitter, Facebook, collaborative OS maps, Google docs, etc.
  • 8. Our Research Goals How users managed the diffusion of the #allertameteoSAR? How did they succeed in creating an hashtag that has been adopted only to share practical information (no expression of solidarity, no general comments)? - give a quantitative account of Twitter activity; - analyze information spread and patterns of influence; - explore the interactions between citizen-generated content, institutional communication, information by media outlets and by celebrities
  • 9. Methods We analyzed the whole dataset of the tweets with hashtag #allertameteoSAR that have been produced during the first week of the Sardinian floods (18-24/11/2013): around 93.091 tweets have been extracted through GNIP “Historical Power Track”. Our research integrates quantitative and qualitative methods. The quantitative side includes automated data analysis and activity metrics; content analysis. Such quantitative methods are integrated with a qualitative tweet analysis (close reading)
  • 10. Findings #1 Tweet volume over time: 81,8% of the tweets during the first two days of the floods The hashtag became #TT
  • 11. Findings #2 Mapping the evolution of crowdsourced emergency management practices How to turn a “generic” Twitter hashtag conversation into a more practical - disaster-recovery oriented – conversation At the beginning the hashtag was used as a general-purpose hashtag; afterwards, some active Twitter users succeeded in transforming it into the “(un)official” hashtag for disaster recovery-related conversations. 3 phases: 1) from 12 pm 18/11: hashtag promotion and diffusion; several tweets saying “please report the troubles (dangers, closed streets, etc.) using the hashtag #allertameteoSAR” 2) from 23 pm 18/11: hashtag ‘cleaning’ and moderation; “no compassionate RT please. It’s time to use the web for information”; “#allertameteoSAR is a channel for URGENT information, not for thoughts. Use #forzasardegna or other hash for useless things” 3) 19/11: hashtag is used to promote a multichannel logic for disaster relief; “please put such information in the map. Otherwise we loose them and they become useless”
  • 12. Findings #3 Users, mentions and RT Unique users: 25.421 (14.545 produced only 1 tweet with #allertameteoSAR) URL: 36,5% of the tweets RT: 84% of the tweets (Bruns and Stieglitz 2014: during natural disasters RT are 55 -70% of the whole tweets) Most mentioned accounts belong to twitstars, popstars and local users Some media and very few institutional accounts are mentioned The most retweeted tweets (N=93, 100 RT or more) represent 15% of the whole db. The majority of those tweets communicate useful information (i.e. emergency numbers; information about recovery centers; request for specific resources, how to create a wi-fi public network etc.)
  • 13. Findings #4 The role of Twistars While a major role in promoting #allertameteoSAR has been played by local “twitstars”, celebrity accounts (well-known Italian pop-stars) appear as the most influential, having received the highest number of mentions and retweets. The 3 most retweeted tweets have been created by 3 Italian pop-stars Marco Mengoni’s tweet has been retweeted 1255 times
  • 14. Most RT users over time (18-20 nov 2013) 0 50 100 150 200 250 300 350 400 11 12 13 14 15 16 17 18 19 20 21 22 23 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 18/11/2013 19/11/2013 20/11/2013 insopportabile Virus1979C Somma di mengonimarco Comune_Cagliari ugocappellacci
  • 15. Findings #6 The role of public institutions The Municipality of Cagliari joined the conversation at 15.56 pm (18/11) Ugo Cappellacci (former President of the Regional Government) joined at 1 am (19/11). Both accounts have been “invited” by the users (through several mentions) to use #allertameteoSAR Italian institutions appear far less influential than “twitstars” or common social media users Twitter users pointed out that Italian institutions were not playing an active role in managing the emergency using social media. The Head of the Italian Civil Protection reacted by minimizing the role of social media and of the digital volunteers Twitter users invited broadcast media (newspapers, tv shows) to cover the event, stressing the distance between Twitter and the mass media agenda
  • 16. Conclusions: digital volunteers and civic engagement During Sardinian floods #allertameteoSAR hashtag has been used to share practical information and to coordinate disaster relief activities Digital volunteers adopted an ecological approach sharing information among several online platforms (Twitter, Facebook, collaborative OS maps, Google doc) #allertameteoSAR hashtag is an example of emergent participatory culture where civic engagement and digital volunteering coexist Citizens as social sensors: user generated contents published on social media produce risks and opportunities Our next step: how can Institutions use such information to effectively communicate during natural disasters?