CrisisNLP: Crisis-related Twitter Dataset (Cumulative)

A Twitter dataset of 25,980 tweets across 10 events, 44 categories, collected by CrisisNLP Research Group via Twitter API (2014-2015). Each record contains tweet text, humanitarian category label, event name, timestamp. Collection of crisis-related tweets from 10 events with humanitarian category labels. Suitable for crisis informatics, humanitarian response, text classification, social media analysis.

#Crisis informatics#Crisisnlp#Humanitarian category

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Analytics

8.2
Flesch–Kincaid grade
US school grade level
11.5
Automated readability index
Frequent terms
nepalrubyphtyphoonhagupitphilippinesnepalearthquakeearthquakesafehelppeoplegodnews__favalancheprayerspraystayrubystormlikequakelandslidelovetyphoonhagupitchilenepalquakeprayforthephilippinestodaygoodstrongdeaddondisasternewhithopeblesswalangpasokindialetraintimekathmanduthankdayknowbaltimoremerstolldeath
Topic clusters

Topic 0

good
think
fuck
happy
day
know
love
like

Topic 1

philippines
typhoon
philippine
pray
typhoonhagupit
help
disaster
weary

Topic 2

chile
earthquake
tsunami
quake
northern
magnitude
napa
california

Topic 3

typhoonhagupit
hagupit
typhoon
typhoonruby
wind
landfall
tacloban
storm

Topic 4

prayforthephilippine
prayfornepal
prayforthephilippines
prayer
safe
pray
soulvultures
prayforchile

Topic 5

landslide
everest
miss
japan
avalanche
flood
kill
dead

Topic 6

prayer
god
nepal
nepalearthquake
victim
people
nepalquake
love

Topic 7

hagupit
philippines
typhoon
weaken
philippine
manila
storm
hit

Topic 8

help
nepal
support
donate
donation
money
need
nepalquakerelief

Topic 9

chute
avalanche
une
mort
terrain
les
glissement
est

Topic 10

vanuatu
cyclone
cyclonepam
pam
pacific
island
tcpam
hit

Topic 11

nepalearthquake
nepalquake
donate
help
appeal
donation
nepal
nepalquakerelief
Show all 26 topics

Topic 12

baltimore
nepal
prayer
nepalearthquake
riot
world
people
heart

Topic 13

walangpasok
class
suspend
tomorrow
level
december
suspension
office

Topic 14

pray
rubyph
safe
god
let
lord
prayer
safety

Topic 15

rubyph
ruby
away
thank
goodbye
rude
welcome
lord

Topic 16

nepalearthquake
nepal
sad
tragedy
news
feel
life
awful

Topic 17

iceland
volcano
bardarbunga
eruption
icelandic
magnitude
earthquake
begin

Topic 18

rain
rubyph
cold
weather
wind
masbate
away
storm

Topic 19

mer
virus
case
saudi
cov
middle
east
health

Topic 20

paris
pfw
fashion
france
spring
wear
des
dior

Topic 21

ruby
typhoon
hagupit
philippine
bulletin
rubyph
philippines
tropical

Topic 22

earthquake
quake
nepal
kathmandu
magnitude
hit
tremor
video

Topic 23

una
por
que
muerto
frana
las
valanga
del

Topic 24

avalanche
snow
ice
bury
rescue
risk
bucket
garage

Topic 25

rubyph
cebu
filipinos
manila
safe
philippines
pray
stay
Top hashtags
#rubyph3.9K
#nepalearthquake1.6K
#nepal1.5K
#hagupit1.3K
#philippines521
#typhoonhagupit486
#nepalquake475
#prayforthephilippines469
#earthquake429
#walangpasok384
#typhoon293
#news239
#typhoonruby144
#thankyoupm137
#mers136
#cyclonepam130
#nepalquakerelief126
#kathmandu119
#indiawithnepal118
#prayfornepal115
Top emoji
󥟏19
􁯱3

Computed over the full corpus.

Record

Catalog key
crisisnlp-cumulative
Authors
Imran, Muhammad; Mitra, Prasenjit; Castillo, Carlos
Year
2016
Source paper
Twitter as a Lifeline: Human-annotated Twitter Corpora for NLP of Crisis-related Messages
DOI / arXiv
10.48550/arXiv.1605.05894
License
See source page for citation/usage terms (CrisisNLP dataset)
Records
25,980
Text corpus
tweet text
Languages
en
Collected
2014-2015 (2010s)
Region
Global (inferred: the platform is used worldwide)

Provenance

Originally published at
https://github.com/ChenBeici/SocialED_datasets/tree/main/raw_data/CrisisNLP link checked

How to cite

BibTeX

@misc{echo2026,
  title  = {ECHO: Exploratory Compendium of Humanity Online},
  author = {Switzer, Braden and Zafarani, Reza},
  year   = {2026},
  url    = {https://echo.directory},
  note   = {Syracuse University}
}

@misc{https://doi.org/10.48550/arxiv.1605.05894,
  doi       = {10.48550/ARXIV.1605.05894},
  url       = {https://arxiv.org/abs/1605.05894},
  author    = {Imran, Muhammad and Mitra, Prasenjit and Castillo, Carlos},
  keywords  = {Computation and Language (cs.CL), Computers and Society (cs.CY), Social and Information Networks (cs.SI), FOS: Computer and information sciences, FOS: Computer and information sciences},
  title     = {Twitter as a Lifeline: Human-annotated Twitter Corpora for NLP of Crisis-related Messages},
  publisher = {arXiv},
  year      = {2016},
  copyright = {arXiv.org perpetual, non-exclusive license}
}

APA

Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory

Imran, M., Mitra, P., & Castillo, C. (2016). CrisisNLP: Crisis-related Twitter Dataset (Cumulative) [Data set]. https://doi.org/10.48550/arXiv.1605.05894

MLA

Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.

Imran, Muhammad, et al. CrisisNLP: Crisis-related Twitter Dataset (Cumulative). 2016, doi.org/10.48550/arXiv.1605.05894.

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