Abstract
This poster 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 visual-ized. It reveals that the trajectories of the migration-related topics are in agreement with historical events. The source codes are available online: https://bit.ly/3dN9ICB.
| Original language | English |
|---|---|
| Journal | CEUR Workshop Proceedings |
| Volume | 2980 |
| Publication status | Published - 1 Jan 2021 |
| Externally published | Yes |
| Event | 2021 International Semantic Web Conference Posters, Demos and Industry Tracks: From Novel Ideas to Industrial Practice, ISWC-Posters-Demos-Industry 2021 - Virtual, Online Duration: 24 Oct 2021 → 28 Oct 2021 |