How people talk about health? Detecting Health Topics from Twitter Streams
Contributo in Atti di convegno
Data di Pubblicazione:
2017
Abstract:
The paper proposes an online clustering algorithm for de-
tecting health-related topics. The method extracts from the
tweets relevant terms and incrementally groups them by tak-
ing into account both term occurrences and tweet age. A
detailed experimentation on the tweets posted by users in
US shows that the method is capable to group tweets ad-
dressing common health issues into the pertinent topic, out-
performing traditional topic model approaches, like Doc-p
and LDA.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
Twitter; Topic Detection; e-Health
Elenco autori:
Pizzuti, Clara; Comito, Carmela
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