Crisis social media data labeled for storm-related information and toponym usage

Research output: Contribution to journalArticlepeer-review

Abstract

Social media provides citizens and officials with important sources of information during times of crisis. This data article makes available labeled, storm-related social media data collected over a six-hour period during a severe storm and F1 tornado that struck Central Pennsylvania on May 1<sup>st</sup>, 2017. Three datasets were collected from Twitter using location, keyword, and network filtering techniques, respectively. Only 2% of the 22,706 total tweets overlap among the datasets, providing researchers with a broader scope of information than normally available when collecting tweets using location (i.e., geotag-based) and keyword filtering alone or in combination during a crisis. Each data collection technique is described in detail, including network filtering which collects data from networks of social media users associated with a geographic area.<br><br>The datasets are manually labeled for information content and toponym usage. The 22,706 tweet IDs, dehydrated for privacy
Original languageEnglish
Pages (from-to)105595
JournalData in Brief
DOIs
StatePublished - Apr 2020

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