Apollo: Twitter stream analyzer of trending hashtags: A case-study of #COVID-19
Abstract:
This poster introduces a new tool named Apollo which analyzes textual information in the geo-tagged twitter streams of trending hashtags using sliding time window. It performs sentiment analysis as well as emotion detection of the opinions of the masses about a trending world wide topic such as #COVID-19, #ClimateChange, #Black-LivesMatter, etc. based on Knowledge Graphs. Apollo currently pro- vides an interactive visualization of the analysis of the trending hashtag #COVID-19.
| Zugehörige Institution(en) am KIT | Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB) |
| Publikationstyp | Zeitschriftenaufsatz |
| Publikationsjahr | 2020 |
| Sprache | Englisch |
| Identifikator | ISSN: 1613-0073 KITopen-ID: 1000127039 |
| Erschienen in | CEUR workshop proceedings |
| Verlag | RWTH Aachen |
| Band | 2721 |
| Seiten | 64-68 |
| Bemerkung zur Veröffentlichung | 19th International Semantic Web Conference on Demos and Industry Tracks: From Novel Ideas to Industrial Practice, ISWC-Posters 2020; Virtual, Online; ; 1 November 2020 through 6 November 2020 |
| Nachgewiesen in | Scopus |
| Globale Ziele für nachhaltige Entwicklung |