Over the summer, Arie Croitoru and myself took part for the first time in the George Mason University Aspiring Scientists Summer Internship Program (ASSIP). We worked with three very talented high-school students who over the course of the seven and a half week program produced some excellent research around the areas of agent-based modeling (ABM), volunteered geographical analysis (VGI), social media and text analysis. An overview of their work can be seen below in the posters and abstracts that the students produced at the end of the internship.
|End of Summer Research Poster Display|
"The news media play a major role in shaping the opinions and beliefs of people around the globe. Alongside more traditional media distribution modes, such as the printed press, in recent years the Internet has begun to play a more important role in news distribution. With the emergence of online news, information can now be disseminated across the globe in real-time. By monitoring such online sources, we can, for the first time, obtain valuable insight into the propagation of news around the world over time, and understand how such media is both produced and consumed. However, obtaining and analyzing this data on a massive scale has proven to be challenging. To address this challenge, we present a novel system for the collection and analysis of news articles. Our system has the capability to extract both metadata and text from a large array of online news sources, and analyze it with respect to themes, locations, time, and language. In order to showcase the utility of our system, we selected 440 prominent news sources across the globe, and monitored their RSS feeds every hour using our system. Through this process we collected roughly 30,000 articles per day over the duration of the study period. To demonstrate the analytical capabilities of our system, we present a case study analysis of coverage of the Islamic State of Iraq and Syria (ISIS) using the system that we developed. In particular, we analyze ISIS-related news using both their content and metadata to show how news propagates over time and space, and explore how the sentiment of the coverage varies."
In a second project Rohan Suri developed an agent-based model to explore the spread and containment of Ebola in a project entitled "A novel computational agent based model for the spread and containment of Ebola Virus Disease". Below is the abstract, poster and a example model run from this project. More information about the model can be found here.
"During the Summer of 2014, the countries of Sierra Leone, Guinea, and Liberia were devastated by an Ebola Virus Disease (EVD) epidemic. Although it killed more than 10,000 people, little is known about EVD dynamics in a macro population. While various attempts have been made to better understand EVD dynamics, such past attempts at modeling EVD exclude an explicit spatial scale, implied general mixing, and did not consider human-to-human interactions. In view of these limitations, this research aims to develop a novel computational agent based model (ABM) to investigate spatial and temporal EVD spread, and to study the effectiveness of control and prevention measures for EVD. In this model, OpenStreetMap (OSM) data was used to construct the physical environment (e.g., road networks), and a realistic population for the three countries was generated from Landscan data and previous surveys. EVD spread was modeled through explicit agent-to-agent interaction and the use of a Suspected-Infected-Exposed-Recovered (SEIR) model"
Example simulation run:
It was a great learning experience from our side by participating in the ASSIP Program.