user generated data on extreme events

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1 Dept. of Systems Engineering & Computer Science, Universidad del Norte, Colombia2 Dept. of Civil and Environmental Engineering, Politecnico di Milano, Como Campus, Italy3 Transport and ICT Global Practice, The World BankUser Generated Data During Extreme EventsMayra Zurbarn1, Maria A. Brovelli2, Danilo Ardagna2, Mattia Manara2, Mark Iliffe3

11The purpose is to provide links and resources

Social media APIs allow access to rich sources of user generated contentThis serves for manyfold applications, specially when it is geo-referenced data, e.g.:Spotting popular locationsDifferent activities within a cityRelevant local newsSentiment analysisMonitoring extreme eventsThis was done in Italy using the Twitter Streaming API for the following events:Monitor precipitation in the countryEarthquake detectionScript openly available at: https://github.com/mazucci/geocollect

Usage of Social Media APIs

22These maps are then validated using reference data obtained either through photo interpretation or field surveys.emphasizes user-generated contentadvancements in GPU (graphics processing unit) technologies and improvements in 3D graphics libraries available virtual globes: Google Earth, Cesium, NASA World Wind -> free and open source vs proprietary

The Twitter Search API:Size limited response per requestNeeds to reconnect on every queryRestricted requests over time; limited at 180 queries per 15 min window

Available at: https://dev.twitter.com/rest/public/search The Twitter Streaming API:Needs only one request and the connection remainsLow latency access up to an estimated 1% of all twitter dataParametrized queries get higher percentage of the full responseOptimized traffic due to less connection attemptsAvailable at: https://dev.twitter.com/streaming/overview Advantages of Using Streamig APIFor Italy around 30,000 geo-referenced tweets are collected daily through the Streaming API

By GEOlab - Geomatics and Earth Observation Laboratory @ POLIMI

33These maps are then validated using reference data obtained either through photo interpretation or field surveys.emphasizes user-generated contentadvancements in GPU (graphics processing unit) technologies and improvements in 3D graphics libraries available virtual globes: Google Earth, Cesium, NASA World Wind -> free and open source vs proprietary

The Twitter Search API:The Twitter Streaming API:

Architecture Comparison


Tecnologies Used for Data CollectionThe web framework for perfectionists with deadlines

&

Streaming response&RetrievesSavesRequest

CSV to processDatabaseApplication


Earthquake in Central ItalyCase Study:

HashtagAppered First AtNumber of Tweets#Italy03:4059#terremoto03:40287#earthquake03:40149#sismo03:4175#Roma03:415#terremotoRoma03:412#quake03:563#Norcia04:095#terremotoItalia8:387

Trends from TweetsFirst reported tweet after the earthquake at aprox. 250 km from the epicentre:

2 minutes after the official time of major earthquake (Mag: 6,0) at 3:36 AM

Popular Hashtags


Intention of the Content

Number of Tweets by ProvincesA total of 498 tweets were related to the earthquake on Aug 24th

Number of Tweets by UsersMost users tweet less than 3 tweets related to the earthquake on Aug 24th

Timelapse of Occurrence of Tweets Related to the Earthquake on Aug 24

From 00 AM to 10 AM


Density Map of Epicentres

*Values calculated using the Kernell formula by Silverman (1986, p. 76, equation 4.5)

Data: A total of 499 earthquakes reported from Aug 17th until Aug 24th of 2016.Source: INGV - http://www.ingv.it/it/


Density Map of Georeferenced Tweets

Precipitations in ItalyCase Study:

Keywords to include while processing: Temporale, acquazzone, diluvio, alluvioneHeatmap of Tweets Distribution


Acquired KnowledgeDuring extreme events, in our case study of earthquakes in central Italy:Users tweet more when they are near the epicentre but on non critical areasPopulation density impacts the content generation: There are more tweets from big citiesAggregating user-generated content aids in understanding users perceptions during extreme events e.g. EMSC - http://www.emsc-csem.orgThe precipitations study shows that are more tweets regarding rain near the Alps Area where it rains more during summer time according to official reportsFor Future Work it is interesting to supervise the behavior during different seasons


Any Questions?Thank you!

user generated data on extreme events

Data & Analytics