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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
Autori di Ateneo:
COMITO CARMELA
PIZZUTI CLARA
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/332157
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