Logo des Repositoriums
 
Konferenzbeitrag

No Mayfly: Detection and Analysis of Long-term Twitter Trends

Lade...
Vorschaubild

Volltext URI

Dokumententyp

Text/Conference Paper

Zusatzinformation

Datum

2023

Zeitschriftentitel

ISSN der Zeitschrift

Bandtitel

Quelle

Verlag

Gesellschaft für Informatik e.V.

Zusammenfassung

The focus of social media is characterized by stories about short-lived breaking news. Often, such mayflies make it hard to keep track of more profound topics that are prevalent over a longer period of time. To tackle this issue we present a method to detect such long-term trends based on temporal networks and community evolution. Connecting those methods with that of trend analysis allows to study the temporal development of trends"

Beschreibung

Ziegler, John; Gertz, Michael (2023): No Mayfly: Detection and Analysis of Long-term Twitter Trends. BTW 2023. DOI: 10.18420/BTW2023-17. Bonn: Gesellschaft für Informatik e.V.. ISBN: 978-3-88579-725-8. pp. 353-364. Dresden, Germany. 06.-10. März 2023

Zitierform

Tags