Tourists are an important asset for the economy of the regions they visit. The answer to the question “where do tourists actually go?” could be really useful for public administrators and local governments. In particular, they need to understand what tourists actually visit, where they actually spend nights, and so on and so forth. In this paper, we introduce an original approach that exploits geo-located messages posted by Twitter users through their smartphones when they travel. Tools developed within the FollowMe suite track movements of Twitter users that post tweets in an airport and reconstruct their trips within an observed area. To illustrate the potentiality of our method, we present a simple case study in which trips are traced on the map (through KML layers shown in Google Earth) based on different analysis dimensions.

Knowledge discovery from geo-located tweets for supporting advanced big data analytics: A real-life experience

CUZZOCREA, Alfredo Massimiliano;
2015

Abstract

Tourists are an important asset for the economy of the regions they visit. The answer to the question “where do tourists actually go?” could be really useful for public administrators and local governments. In particular, they need to understand what tourists actually visit, where they actually spend nights, and so on and so forth. In this paper, we introduce an original approach that exploits geo-located messages posted by Twitter users through their smartphones when they travel. Tools developed within the FollowMe suite track movements of Twitter users that post tweets in an airport and reconstruct their trips within an observed area. To illustrate the potentiality of our method, we present a simple case study in which trips are traced on the map (through KML layers shown in Google Earth) based on different analysis dimensions.
9783319237800
9783319237817
http://link.springer.com/book/10.1007/978-3-319-23781-7/page/2
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2872371
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