Search results for "Twitter data"
showing 3 items of 3 documents
Marked Hawkes processes for Twitter data
2022
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.
Twitter spam account detection by effective labeling
2019
In the last years, the widespread diffusion of Online Social Networks (OSNs) has enabled new forms of communications that make it easier for people to interact remotely. Unfortunately, one of the first consequences of such a popularity is the increasing number of malicious users who sign-up and use OSNs for non-legit activities. In this paper we focus on spam detection, and present some preliminary results of a system that aims at speeding up the creation of a large-scale annotated dataset for spam account detection on Twitter. To this aim, two different algorithms capable of capturing the spammer behaviors, i.e., to share malicious urls and recurrent contents, are exploited. Experimental r…
The mobility network of European tourists: a longitudinal study and a comparison with geo-located Twitter data
2018
Purpose This paper aims to provide a network study of the structural and dynamical characteristics of tourism flows in Europe from 1995 to 2012. Design/methodology/approach Travels in Europe were studied by following the network science research paradigm and by focusing on the whole network of intra-European tourism destinations. Network analysis was used to map and reveal the pattern of connections between states as shaped by bilateral tourism flows. Data were provided by the United Nations World Tourism Organization, and the data were integrated with tourism data available from national statistical offices of the individual countries, when necessary. Findings For 2012, results obtained f…