6533b7dafe1ef96bd126e742
RESEARCH PRODUCT
Marked Hawkes processes for Twitter data
Andrea SimonettiNicoletta D'angeloGiada Adelfiosubject
Settore SECS-S/06 -Metodi Mat. dell'Economia e d. Scienze Attuariali e Finanz.Twitter data self-exciting point processes textual analysis Hawkes modelsSettore SECS-S/01 - Statisticadescription
In this paper, we propose to model retweet event sequences using a marked Hawkes process, which is a self-exciting point process where the occurrence of previous events in time increases the probability of further events. The aim is to analyse Twitter data combining temporal point processes theory and textual analysis. Since each retweet event carries a set of properties, we mark the process by different characteristics drawn from the textual analysis, finding that the tone of the description of the Twitter user is a good predictor of the number of retweets in a single cascade.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2022-01-01 |