COMPUTATIONAL SOCIAL SCIENCE RESEARCH COLLOQUIUM /COLLOQUIUM IN COMPUTATIONAL AND DATA SCIENCES – #pray4victims: Consistencies In Response to and Automatically Identifying Diverse Information Needs During Disasters on Twitter – Cody Buntain
Computational Social Science Research Colloquium /
Colloquium in Computational and Data Sciences
Post Doctoral Researcher
New York University’s Social Media and Political Participation Lab
#pray4victims: Consistencies In Response to and Automatically
Identifying Diverse Information Needs During Disasters on Twitter
Friday, March 08, 2019, 3:00 p.m.
Center for Social Complexity Suite, 3rd Floor Research Hall
All are welcome to attend.
This talk presents commonalities in response across disasters in online social networks (OSNs) and Twitter specifically.
After presenting an algorithm for extracting vocabularies across disasters, we extract type-specific vocabularies for terrorist attacks, earthquakes, and climate-related disasters between 2012 and 2017.
Within similar disasters, commonalities emerge: terrorism responses reference the “attack” and law enforcement, earthquake responses mention the quake and its magnitude, and climate-related responses include safety and requests for aid.
Across disaster types, tweets regularly mention victims/affected and prayer, consistent with communal coping and social support in crisis aftermath.
Using these disaster-type vocabularies, we study Twitter as an alternate measure for severity, correlating casualties to Twitter volume.
These vocabularies better correlate with casualties than baseline crisis lexica, especially in western countries.
Twitter response and casualties diverge at the extreme, and Twitter response is stronger in Western countries, suggesting perceived severity is driven by additional factors.
These vocabularies also potentially represent disaster-type-specific information needs, which we then roll into a machine learning task for automatically identifying crisis-related information in Twitter data.
Cody Buntain received his PhD from the Computer Science Department at the University of Maryland and is a postdoctoral researcher with New York University’s Social Media and Political Participation Lab. His primary research areas apply large-scale computational methods to social media and other online content, specifically studying how individuals engage socially and politically and respond to crises and disaster in online spaces. Current problems he is studying include cross-platform information flows, network structures, temporal evolution/politicization of topics, misinformation, polarization, and information quality. Recent publications include papers on influencing credibility assessment in social media, consistencies in social media’s response to crises, the disability community’s use of social networks for political participation, and characterizing gender and direction in online harassment.