Every day a huge amount of data is generated by users of social media platforms, like Facebook, Twitter and so on. Analyzing data posted by people interested in a given topic or event allows inferring patterns and trends about people behaviors on a very large scale. These posts are often geotagged, this way enabling mobility pattern analysis. In this work, we investigate the use of Process Mining techniques to support the discovery and the analysis of mobility patterns of social media users. We discuss the results obtained analyzing posts of Instagram users who visited EXPO 2015, the Universal Exposition hosted in Milan, Italy, from May to October 2015
Report de RecercaLocation Based Social Networks (LBSN) like Twitter or Instagram are a good source f...
International audienceData mining techniques can extract useful activity and travel information from...
Report de recercaLocation Based Social Networks (LBSN) like Twitter or Instagram are a good source f...
Every day a huge amount of data is generated by users of social media platforms, like Facebook, Twit...
Every day a huge amount of data is generated by users of social media platforms, like Facebook, Twit...
Understanding the characteristics of tourists’ movements is essential for tourism destination manage...
The development of social networks such as Twitter, Facebook and Google+ allow users to share their ...
Location Based Social Networks (LBSN) like Twitter or Instagram are a good source for user spatio-te...
Social media data with geotags can be used to track people's movements in their daily lives. By...
The spread of Internet and online social media has created a huge amount of data able to provide new...
This work investigates whether the user-generated data from multiple sources, such as smart cards an...
© 1995-2012 IEEE. Social media data with geotags can be used to track people's movements in their da...
Understanding the patterns underlying human mobility is of an essential importance to applications l...
Location Based Social Networks (LBSN) have become an interesting source for mining user behavior. Th...
Understanding human mobility patterns is of great importance for urban planning, traffic management,...
Report de RecercaLocation Based Social Networks (LBSN) like Twitter or Instagram are a good source f...
International audienceData mining techniques can extract useful activity and travel information from...
Report de recercaLocation Based Social Networks (LBSN) like Twitter or Instagram are a good source f...
Every day a huge amount of data is generated by users of social media platforms, like Facebook, Twit...
Every day a huge amount of data is generated by users of social media platforms, like Facebook, Twit...
Understanding the characteristics of tourists’ movements is essential for tourism destination manage...
The development of social networks such as Twitter, Facebook and Google+ allow users to share their ...
Location Based Social Networks (LBSN) like Twitter or Instagram are a good source for user spatio-te...
Social media data with geotags can be used to track people's movements in their daily lives. By...
The spread of Internet and online social media has created a huge amount of data able to provide new...
This work investigates whether the user-generated data from multiple sources, such as smart cards an...
© 1995-2012 IEEE. Social media data with geotags can be used to track people's movements in their da...
Understanding the patterns underlying human mobility is of an essential importance to applications l...
Location Based Social Networks (LBSN) have become an interesting source for mining user behavior. Th...
Understanding human mobility patterns is of great importance for urban planning, traffic management,...
Report de RecercaLocation Based Social Networks (LBSN) like Twitter or Instagram are a good source f...
International audienceData mining techniques can extract useful activity and travel information from...
Report de recercaLocation Based Social Networks (LBSN) like Twitter or Instagram are a good source f...