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Table 1 Data description

From: Quantifying human mobility resilience to extreme events using geo-located social media data

Type

Disaster Name

Disaster Location

No. of Tweets

No. of Users

Hurricane

Sandy (all tweets)

USA

52,493,130

13,745,659

Sandy (geo-tagged tweets)

USA

24,149,780

5,981,012

Earthquake

Bohol (Bohol)

Bohol, Philippines

114,606

7942

Iquique (Iquique)

Iquique, Chile

15,297

1470

Napa (Napa)

Napa, USA

38,019

1850

Typhoon

Wipha (Tokyo)

Tokyo, Japan

849,173

73,451

Halong (Okinawa)

Okinawa, Japan

166,325

5,124

Kalmaegi (Calasiao)

Calasiao, Philippines

21,698

1,063

Rammasun (Manila)

Manila, Philippines

408,760

27,753

Winter storm

Xaver (Norfolk)

Norfolk, Britain

115,018

8498

Xaver (Hamburg)

Hamburg, Germany

15,054

2745

Storm (Atlanta)

Atlanta, USA

157,179

15,783

Thunder storm

Storm (Phoenix)

Phoenix, USA

579,735

23,132

Storm (Detroit)

Detroit, USA

765,353

15,949

Storm (Baltimore)

Baltimore, USA

328,881

14,582

Wildfire

New South Wales (1)

New South Wales, Australia (1)

64,371

9246

New South Wales (2)

New South Wales, Australia (2)

34,157

4147