Marina Kogan

Think Local, Retweet Global: Retweeting by the Geographically-Vulnerable during Hurricane Sandy

Hurricane Sandy wrought

Finding the Way to OSM Mapping Practices: Bounding Large Crisis Datasets for Qualitative Investigation

6 billion in damage, took 162 lives, and displaced 776,000 people after hitting the US Eastern seaboard on October 29, 2012. Because of its massive impact, the hurricane also spurred a flurry of social media activity, both by the population immediately affected and by the globally convergent crowd. In this paper we explore how retweeting activity by the geographically vulnerable differs (if at all) from that of the general Twitter population. We investigate whether they spread information differently, including what and whose content they chose to propagate. We investigate whether the Twitter-based relationships are preexisting or if they are newly formed because of the disaster, and if so if they persist. We find that the people in the path of the disaster favor in their retweeting locally-created tweets and those with locally-actionable information. They also form denser networks of information propagation during disaster than before or after.

EPIC-OSM: A Software Framework for OpenStreetMap Data Analytics

OpenStreetMap (OSM) is the most widely used volunteer geographic information system. Although it is increasingly relied upon during humanitarian response as the most up-to-date, accurate, or accessible map of affected areas, the behavior of the mappers who contribute to it is not well understood. In this paper, we explore the work practices and interactions of volunteer mappers operating in the high-tempo, high-volume context of disasters. To do this, we built upon and expanded prior network analysis techniques to select high-value portions of the vast OSM data for further qualitative analysis. We then performed detailed content analysis of the identified activity and, where possible, conducted interviews with the participants. This research allowed the identification of seven distinct mapping practices that can be classified according to dimensions of time, space, and interpersonal interaction. Our work represents a baseline for future research about how OSM crisis mapping practices have evolved over time.

Hazardous Weather Prediction and Communication in the Modern Information Environment

An important area of work in big data software engineering involves the design and development of software frameworks for data-intensive systems that perform large-scale data collection and analysis. We report on our work to design and develop a software framework for analyzing the collaborative editing behavior of OpenStreetMap users when working on the task of crisis mapping. Crisis mapping occurs after a disaster or humanitarian crisis and involves the coordination of a distributed set of users who collaboratively work to improve the quality of the map for the impacted area in support of emergency response efforts. Our paper presents the challenges related to the analysis of OpenStreetMap and how our software framework tackles those challenges to enable the efficient processing of gigabytes of OpenStreetMap data. Our framework has already been deployed to analyze crisis mapping efforts in 2015 and has an active development community.

“Sometimes da #beachlife ain't always da wave”: Understanding People’s Evolving Hurricane Risk Communication, Risk Assessments, and Responses Using Twitter Narratives

CapsuleUnderstanding the dynamic, interconnected processes that characterize the modern hazard information system can transform the creation, communication, and use of weather and climate information.

Digital Traces of Online Self-Organizing and Problem Solving in Disaster

AbstractThis article investigates the dynamic ways that people communicate, assess, and respond as a weather threat evolves. It uses social media data, which offer unique records of what people convey about their real-world risk contexts. Twitter narratives from 53 people who were in a mandatory evacuation zone in a New York City neighborhood during Hurricane Sandy in 2012 were qualitatively analyzed. The study provides rich insight into the complex, dynamic information behaviors and risk assessments of people at risk, and it illustrates how social media data can be collected, sampled, and analyzed to help provide this understanding. Results show that this sample of people at significant risk attended to forecast information and evacuation orders as well as multiple types of social and environmental cues. Although many tweeted explicitly about the mandatory evacuation order, forecast information was usually referenced only implicitly. Social and environmental cues grew more important as the threat approac...

Assessing Long-Term Effects of Inquiry-Based Learning: A Case Study from College Mathematics

Natural disasters are associated with breakdown of existing structures, but they also result in creation of new social ties in the process of self-organization and problem solving by those affected. In highly-distributed setting of social media, collaborative arrangements must depend on the aspects of work that facilitate (or not) the creation of a shared information space-such as an explicit shared site of work and visible, legible record of the activity. In my dissertation I investigate what organizational structures emerge through problem solving in the context of more or less explicit shared site of work and more or less visible record of activity.