The document discusses using Twitter data to analyze incidents in real-time to improve crisis management. It presents a case study of analyzing tweets during a heavy storm that hit the Pukkelpop music festival in Belgium in 2011. Over 150,000 tweets were posted over two days. The analysis found that tweets provided early warnings of weather before it hit, shared photos of damage within an hour of the incident, and rumors of casualties which were later confirmed by news sources. A hashtag for community support (#Hasselthelpt) emerged and was widely used to coordinate help for those affected. The study demonstrates how social media can provide timely information but also shows the need to verify rumors.
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Towards a realtime Twitter analysis during crises: the case of PP11
1. Towards a realtime Twitter analysis: The case of PP11
Teun Terpstra, HKV
Arnout de Vries, TNO
Flood Risk 2012
Richard Stronkman, Twitcident
November 22, Rotterdam
WWW.FLOODCONTROL2015.COM >
SLIDE
2. Discussion and future work
1 minute ago
Results: early warning, facts and feelings, resilience
5 minutes ago
Analysis (Pukkelpop) and research method (Twitcident)
10 minutes ago
Goal: “Monitor and analyze Twitter during incidents in
real-time to improve crisis management”
15 minutes ago
Social sensors and citizen journalism
20 minutes ago
3. M Bouman 3
TNO Nieuwe
10 januari 2011
huisstijl
SLIDE
7. Social media & emergency management
Red river floods
SLIDE 7
8. Moerdijk Fire, January 2011
First hour: 5000 tweets
Total 5 January 2011: 70.000 tweets
Tool: Twitcident
SLIDE 8
9. Project X Haren, September 2012
Bron: http://www.mobypicture.com/user/harro/ (Harro Ranter)
SLIDE 9
10. Flood hazard, Friesland / Groningen
January 2012
Messages per hour (34.000 total)
Tool: Gilgamesh
SLIDE
11.
12. Law of “When hell breaks loose”
“Hell” = Culpability x Relevance x Mediagenicity2
(Study “Van gebeurtenis tot crisis, wanneer breekt de pleuris uit?” MCDm 2002)
crisis (communication)
manager
17. Pukkelpop Twitter visual analysis
Selection of 96.957 tweets between noon and midnight
2. Damage and casualties
Tweets /min
Messages about
(rumours on) casualties
and deaths
1. Early warning
3. ‘Community resilience’
‘Dangerous weather’
messages as early People offering help in
indicators various ways (e.g.
twitterlists)
94,109
2,848 tweets
tweets
12:00 18:15 00:00
SLIDE 17
18. 1. Early warning? without retweets
tweets
Tussen 17:38 en 18:15
retweets
• 311 retweets
• 277 (89%) RT@ShannonLeto
2011-08-18 17:38:19
You ready Pukkelpop?! Might be a wet one out there! Slip-n-
slide-an-dog-an-you!! Remember that one @jaredlet
SLIDE 18
19. 1. Early warning
343 tweets (ex retweets) between 4:45 and 6:15 PM
56 tweets (16%) related to the changing weather conditions.
35 (10%) observations of extreme weather conditions (e.g. cloud-bursts, hail,
storm and lightning in nearby places like Brussels, Leuven, and Hasselt).
22 tweets (6%) reflected worries that the storm might hit on Pukkelpop.
SLIDE
20. 2. Damage: photo’s from eye witnesses
First hour: 674 tweets
64% are retweets
17% request more detailed
information
1,071 (54%) tweets contained
hyperlinks to other social /
news media showing some
of the damaged properties
20
21. 2. Damage
Reaches 10.000 followers within three minutes (119 retweets)
18:31 19:01
– Official news media (VRT): festival interrupted and possibly a tent collapsed
– Information on Twitter available approximately 40 minutes earlier
SLIDE
21
22. 2. Casualties
7:50 PM
Total tweets 256 TPM
13 minutes: ‘Death’ tweets 237 TPM
• 1342 tweets about casualties
• 52% RT spreading confirmations
• Other tweets expressed shock,
agitation, astonishment and hope
18:52 19:37
rumors journalists and news
about media editors confirm
deaths multiple deaths
19:12 ‘rozestadfm’
“BREAKING NEWS: Serious injuries and deaths at Pukkelpop in Hasselt (B)
during a heavy storm #storm #pukkelpop #events #belgium #hasselt”
‘rumor, ‘speculate’, ‘confirm’, ‘official news’, ‘source’ and ‘irresponsible’
SLIDE 22
23. 3. Community resilience
PatriceF Are you at Pukkelpop and in need of aid? Check @Deborahhasselt @iworx @patricef #pp11 20:19
#pukkelpop #hasselthelpt (RT is appreciated)
PatriceF Do you want to help? Use #hasselthelpt to support festivalgoers at #p11 20:27
jhml #hasselthelpt RT @theonehitwonder: If someone needs a place to sleep, let me know. We are 20:27
from Hasselt #pp11
• 9315 tweets #Hasselthelpt (74% retweets)
• #Genthelpt, #Brusselhelpt, …
• Creation of Twitterlists (e.g. PatriceF)
• Sharing of phone numbers
• Creation of Twitter accounts
3. ‘Community resilience’
SLIDE 23
24. Discussion
Festival goers were taken by surprise, so it seems. But (weak) signals were
there.
Retweets accounted for large amounts of tweets on damage and casualties and
only occurred when
pictures (in case of damage) or
links to official news sites (in case of casualties) were available.
This suggests social norms on twitter prevent propagation of unverified
information about delicate topics.
Solidarity is important in coping with disasters (Starbird et al). Within 2 hours
the #hasselthelpt initiative was followed massively. This suggests social media
can facilitate community resilience that originate from nearby people.
Twitter monitoring could enable crisis managers to confirm or refute rumors
and take emotional responses into account in crisis communications.
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25. Implications for crisis management
Visual analysis provide a good start to identify abnormalities
Filtering on damage could have provided pictorial 'evidence'
# of retweets attract attention and point toward a hot topic from a
'trusted' source, and news about damage or casualties mostly have
high propagation
Not just about technology: organizational solutions needed for
embedding social media usage in crisis communications, such as
more experience, knowledge and policies.
WWW.FLOODCONTROL2015.COM SLIDE 25
26. Future research
Early detection and early warning:
Examples: Queensday, (death) threats and weather conditions
Filters for damage and casualties need to be verified for other
incidents. New topic filters such as resilience need more research.
Retweets and source credibility are indeed related. Images and
links, besides the author, play an important role in assessing
credibility.
Indicators for assessing real-time credibility seem possible
and are valuable for crisis response teams.
WWW.FLOODCONTROL2015.COM SLIDE 26
29. TIMELINE
First relevant
pictures showing
Start incident: Reports damage (collapse
heavy rainfall about of tent)
damage Large amounts of
Indications of and rumour spread about Initiation of
heaviness of casualties #deaths #Hasselthelpt
storm GSM network
Reports Deaths semi- is fixed
heading to confirmed by
about “SMS use
~ 21:00
Pukkelpop individual
19:15
only” is asked
16:22
19:38
20:19
18:35
deaths
18:30
19:12
18:15
from citizens journalist for
August 18th 2011 August 19th
19th aug12:00 AM
Fire depts Sint
21:56
20:06
20:50
19:40
19:53
18:24
19:19
19:03
Truiden say 6
@Pukkelpop
deaths and
message with
Hasselt says 1
“
death 7 injured
Belgian press handelingsper Official news:
started reporting spectief” 5 deaths, tens
@Pukkelpop
First pictures (individual (phone injured,
first message
showing panic accounts) number and festival
since incident
URL) cancelled
Press
conference
Announcement (TV): 2 deaths
Dutch press that festival is and 40 injured
starts cancelled for the
reporting night
WWW.FLOODCONTROL2015.COM SLIDE 29
Editor's Notes
JANUARY 11, 2010 WWW.FLOODCONTROL2015.COM SLIDE
this is just a snap shot of today, consider the future with the current adoption of social media! TITEL VAN DE PRESENTATIE 16-01-13 09:28
Prior research: twitter adoption in crises (hughes, palen), floodings (starbird), haiti (starbird) Hurricane irene, moerdijk, virginia floods, london riots, etc.
Fire incident in a company working with chemical substances
Project X was a Facebook event encouraging people to come to the city Haren in order to celebrate a 16 year old girl’s birthday The event resulted in a riot.
Improved situational awareness. Smart filtering needed: from hand analysis towards automated analysis. red river floods, oklahoma wildfires: analysis by hand
http://www.youtube.com/watch?v=xtw2bskw4e8
1% of total tweets are geo tagged 79% of total tweets originate from festival site (2 hours before impact) First 15 minutes after incident, 77% of geotagged originate from festival site, then decreases to 15 and 4 % as messages spread across the world. TITEL VAN DE PRESENTATIE 16-01-13 09:28
Peaks of nearly 600 tweets about incident per minute. Real-time interpretation would have been impossible by hand. TITEL VAN DE PRESENTATIE 16-01-13 09:28
TITEL VAN DE PRESENTATIE 16-01-13 09:28
- Damage reporting Keywords like collapse, destroy, ravage, devastate and conjugations of these terms Tweet of user ”c_concepts” at 6.31, reaches audience of 10.000 followers in 3 minutes, and 119 retweets over time Until 7.01 pm official news media message( screenshot?) With same info that was available 40 minutes before from festivalgoers. 54% of tweets contain hyperlinks to news media websites or photo sharing sites, to show damaged properties. - Casualty reporting and rumors about deaths About 30 casualty related tweets per minute after start incident Rumors on deaths: The tweet of “Rozestadfm” from 7:12 initiated a rumor, but was answered with 60 retweets of which 30% questioned validity of the statement Typical keywords to express doubts were rumor, speculate, irresponsible 118 phrased their doubts in the form of a question, requesting official source verification. 7:37 increase in activity, with peak of 256 tweets per minute about deaths, after official news media confirmed there were multiple deaths, 52% of these were retweets, where others expressed shock, agitation, astonishment and hope. 3,676 (27%) of casualty related tweets Contained hyperlinks to news articles that confirm the number of deaths and casualties. TITEL VAN DE PRESENTATIE 16-01-13 09:28
Patricef Twitterlists to form a suplly demand for food, places to sleep, showers, clothing, internet access, transportation, etc. Phone numbers were shared, some users offering help created their first twitter account Retweeted 424 times, 9,315 tweets contained #hasselthelpt, the nearby village and soon #genthelpt and #brusselhelpt followed. Sentiment analysis indicated positive responses, expressed by spect, great, fantastic, nice, love, homage, heartwarming, impressed. TITEL VAN DE PRESENTATIE 16-01-13 09:28