ITFLOWS FIZ researchers Yiyi Chen and Mehwish Alam co-authored and published a conference paper and poster during the highly prestigious International Semantic Web Conference. The paper itself, focuses on capturing the temporal evolution of migration-related topics on relevant tweets. It uses Dynamic Embedded Topic Model (DETM) as a learning algorithm to perform a quantitative and qualitative analysis of these emerging topics. TweetsKB is extended with the extracted Twitter dataset along with the results of DETM which considers temporality. These results are then further analyzed and visualized. It reveals that the trajectories of the migration-related topics are in agreement with historical events.
In order to view the conference outputs, please click on the following links: