Analyzing a fake news authorship network

This project synthesizes a set of 246 fake news websites previously identified in three earlier research projects. From this dataset, we extract a set of all authors who have written for these sites in 2016. This authorcentric dataset is itself a contribution that will allow future analysis of the fake news ecosystem. Based on the data we collected, we construct a network of fake news sites, linking them if they shared a common author. Our analysis shows a tight cluster of author-sharing sites, with a small core set of sites sharing dozens of authors

Tell Your Robot What To Do: Evaluation of Natural Language Models for Robot Command Processing

The use of natural language to indicate robot tasks is a convenient way to command robots. As a result, several models and approaches capable of understanding robot commands have been developed, which however complicates the choice of a suitable model for a given scenario. In this work, we present a comparative analysis and benchmarking of four natural language understanding models - Mbot, Rasa, LU4R, and ECG. We particularly evaluate the performance of the models to understand domestic service robot commands by recognizing the actions and any complementary information in them in three use cases: the RoboCup@Home General Purpose Service Robot (GPSR) category 1 contest, GPSR category 2, and hospital logistics in the context of the ROPOD project