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.
How people talk about health? Detecting Health Topics from Twitter Streams
Carmela Comito;Clara Pizzuti;
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.File in questo prodotto:
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