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Apollo: Twitter stream analyzer of trending hashtags: A case-study of #COVID-19

Alam, M.; Kaschura, M.; Sack, H.

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.

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Verlagsausgabe §
DOI: 10.5445/IR/1000127039
Veröffentlicht am 27.12.2020
Cover der Publikation
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 CEUR Workshop Proceedings
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
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