Using Twitter to Analyze the Effect of Hurricanes on Human Mobility Patterns
Abstract
:1. Introduction
2. Related Literature
3. Data and Methods
3.1. Study Areas
3.1.1. Hurricane Harvey
3.1.2. Hurricane Matthew
3.2. Data Collection and Preparation
3.3. Data Analysis
4. Results
4.1. Trip Distances
4.2. Activity Spaces
4.3. Tweet Numbers around Supply Related Points of Interest
4.4. Hashtags Use
5. Concluding Discussion and Future Work
Author Contributions
Funding
Conflicts of Interest
References
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Hurricane | Period | User Filter Applied | User Filter Not Applied | ||
---|---|---|---|---|---|
# Users | # Tweets | # Users | # Tweets | ||
Harvey (Houston) | 14 August 2017–19 September 2017 | 75 | 13,980 | 8601 | 34,294 |
Matthew (Miami-Dade) | 22 September 2016–20 October 2016 | 69 | 13,555 | 11,407 | 55,122 |
Matthew (N/S Carolina) | 24 September 2016–23 October 2016 | 49 | 4436 | 8582 | 29,432 |
Period | Houston | Miami-Dade | North and South Carolina | ||||||
---|---|---|---|---|---|---|---|---|---|
Mean | Median | p-Value | Mean | Median | p-Value | Mean | Median | p-Value | |
Before | 16 | 10 | 0.005 | 7 | 4 | 0.019 | 17 | 5 | 0.124 |
During | 11 | 5 | - | 5 | 2 | - | 11 | 3 | - |
After | 17 | 9 | 0.025 | 9 | 6 | <0.001 | 24 | 5 | 0.021 |
Period | Houston | Miami-Dade | North and South Carolina | ||||||
---|---|---|---|---|---|---|---|---|---|
Mean | Median | p-Value | Mean | Median | p-Value | Mean | Median | p-Value | |
Before | 11.1 | 8.6 | 0.015 | 5.9 | 4.7 | 0.064 | 10.2 | 2.9 | 0.045 |
During | 6.64 | 1.9 | - | 3.9 | 3.6 | - | 2.2 | 1.3 | - |
After | 12.6 | 11.3 | 0.005 | 4.0 | 3.1 | 0.281 | 16.9 | 3.2 | 0.093 |
Hurricane/Study Area | Before | During | After | |||
---|---|---|---|---|---|---|
Hashtag | Freq. | Hashtag | Freq. | Hashtag | Freq. | |
Harvey/Houston | ireallybreakmusic | 16 | Repost | 129 | GloryFitness | 28 |
Repost | 16 | hurricaneharvey | 23 | ireallybreakmusic | 24 | |
Mp3waxx | 14 | prayforhouston | 18 | Repost | 21 | |
GloryFitness | 6 | houston | 9 | fitnessmotivation | 19 | |
houston | 6 | houstonstrong | 8 | MP3Waxx | 19 | |
realtor | 4 | texas | 7 | fitnessmodel | 18 | |
Houston | 4 | hurricane | 7 | breakfast | 10 | |
fitnessmodel | 4 | HurricaneHarvey | 5 | FollowTheSmell | 6 | |
jessegreene | 4 | Hurricaneharvey | 4 | ClientMelissaE | 6 | |
fitnessmotivation | 4 | prayfortexas | 4 | Houston | 5 | |
Matthew/Miami-Dade County | southbeach | 9 | miamibeach | 14 | Take1TakeOver | 33 |
miamibeach | 9 | miami | 11 | miami | 8 | |
beachlife | 9 | beachlife | 10 | BarackObama | 5 | |
southbeachlocal | 9 | southbeachlocal | 10 | TagsForLikes | 5 | |
usa | 8 | southbeach | 10 | ingodwetrust | 5 | |
tropical | 8 | beachvolleyball | 8 | weedvision | 5 | |
beachvolleyball | 8 | tropical | 7 | daytrader | 5 | |
palmtrees | 6 | nature_perfection | 6 | ironteam | 5 | |
Miami | 6 | hurricanematthew | 6 | fuck925 | 5 | |
fitness | 6 | matthew | 6 | StrongerTogether | 5 | |
Matthew/North and South Carolina | nofilter | 4 | hurricanematthew | 21 | fccstudentministry | 4 |
beachlife | 3 | HurricaneMatthew | 5 | tunarun2016 | 3 | |
uncw | 3 | surfcity | 4 | wilmingtonnc | 3 | |
sundaymorningservice | 3 | northcarolina | 4 | bleachmyfilm | 3 | |
goodmorning | 3 | matthew | 4 | kurebeach | 2 | |
knottsisland | 3 | surfcitync | 3 | TheMatrimony | 2 | |
sunrise | 3 | OnePiece | 2 | wilmington | 2 | |
Legend | 2 | charleston | 2 | outerbanks | 2 | |
thankyou | 2 | h2ography | 2 | Chicago | 2 | |
freedomthinkers | 2 | topsailisland | 2 | PoeticJustice | 2 |
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Ahmouda, A.; Hochmair, H.H.; Cvetojevic, S. Using Twitter to Analyze the Effect of Hurricanes on Human Mobility Patterns. Urban Sci. 2019, 3, 87. https://doi.org/10.3390/urbansci3030087
Ahmouda A, Hochmair HH, Cvetojevic S. Using Twitter to Analyze the Effect of Hurricanes on Human Mobility Patterns. Urban Science. 2019; 3(3):87. https://doi.org/10.3390/urbansci3030087
Chicago/Turabian StyleAhmouda, Ahmed, Hartwig H. Hochmair, and Sreten Cvetojevic. 2019. "Using Twitter to Analyze the Effect of Hurricanes on Human Mobility Patterns" Urban Science 3, no. 3: 87. https://doi.org/10.3390/urbansci3030087