Analyzing the Evolution of Disinformation Content on Facebook - a Pilot Study

Disinformation spread on social media generates a truly massive amount of content on a daily basis, much of it not quite duplicated but repetitive and related. In this paper, we present an approach for clustering social media posts based on topic modeling in order to identify and formalize an underlying structure in all the noise. This would be of great benefit for tracking evolving trends, analyzing large-scale campaigns, and focusing efforts on debunking or community outreach. The steps we took in particular include harvesting through CrowdTangle huge collection of Facebook posts explicitly identified as containing disinformation by debunking experts, following those links back to the people, pages and groups where they were shared then collecting all posts shared on those channels over an extended period of time. This generated a very large textual dataset which was used in the topic modeling experiments attempting to identify the larger trends in the available data. Finally, the results were transformed and collected in a Knowledge Graph for further study and analysis. Our main goal is to investigate different trends and common patterns in disinformation campaigns, and whether there exist some correlations between some of them. For instance, for some of the most recent social media posts related to COVID-19 and political situation in Ukraine. © 2022 Copyright for this paper by its authors.

Shader Injection for Instanced 3D Models

Creating a large-scale virtual world requires the management of many graphical objects. We are building an educational COVID-19 simulator of a procedurally generated city. One way to render effectively the large number of buildings and people is to clone them. This paper presents an approach of injecting custom code into the programs, run by the graphical processor. This code randomizes the shape of the otherwise identical graphical objects and the result is a collection of various buildings and people. © 2021 IEEE.

Visual Educational Simulator of Pandemic: Work in Progress

This paper presents the design and development of a visual pandemic simulator, which is still a work in progress. The goal is two-fold: to make a simulator capable of demonstrating various pandemic and social situations including the current COVID-19 outbreak;and to serve as a platform for activities for graduate and undergraduate education. The paper presents the main steps of building the simulator and the corresponding educational opportunities. © 2021, Springer Nature Switzerland AG.