Work

Expanding Awareness: Comparing Location, Keyword, and Network Filtering Methods to Collect Hyperlocal Social Media Data

Year: 2019

Type: conference-paper

Abstract: Opportunities to collect real-time social media data during a crisis remain limited to location and keyword filtering despite the sparsity of geographic metadata and the tendency of keyword-based methods to capture information posted by remote rather than local users. Here we introduce a third, network filtering method that uses social network ties to infer the location of social media users in a geographic community and collect data from networks of these users during a crisis. In this paper we compare all three methods by analyzing the distribution of situational reports of infrastructure damage and service disruption across location, keyword, and network-filtered social media data during a weather emergency. We find that network filtering doubles the number of situational reports collected in real-time compared to location and keyword filtering alone, but that all three methods collect unique reports that can support situational awareness of incidents occurring across a community.

Source: Hawaii International Conference on System Sciences (HICSS)

DOI: 10.24251/hicss.2019.325

Authors: Rob Grace, Shane Halse, William Aurite, Aurélie Montarnal, Andrea Tapia

Institution: Pennsylvania State University

Language: English

Topic: Public Relations and Crisis Communication

Subfield: Communication

Field: Social Sciences

Domain: Social Sciences

SDG: Sustainable cities and communities

Open Access status: hybrid

Funder: National Science Foundation