A network-based ranking approach to discover places visited by tourists from geo-located tweets

Cortesi, Nicola and Gotti, Kevin and Psaila, Giuseppe and Burini, Federica and Lwin, Khin T. and Hossain, Mohammed Alamgir (2018) A network-based ranking approach to discover places visited by tourists from geo-located tweets. In: 2017 11th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), Malabe, Sri Lanka.

Full text not available from this repository.
Official URL: https://doi.org/10.1109/SKIMA.2017.8294111

Abstract

This work analyses the existing connections between public spaces in the city, by developing a new ranking method based on the information related to citizens' movement in the urban space using social media. We propose a NodeRank algorithm, a modified version of the Page-Rank algorithm, which introduces a new reticular perspective as it considers both incoming links in a page, and outgoing links too. The proposed algorithm has been tested with a dataset of geolocated Tweets collected in previous research. Results indicate that the proposed Node-Rank Algorithm offers an excellent performance in identifying the places of greatest interest from the point of view of Twitter users and it is useful to reconstruct the network between public spaces in the city.

Item Type: Conference or Workshop Item (Paper)
Keywords: Urban areas, Social network services, Big Data, Europe, Electronic mail, Web search, Engines
Faculty: ARCHIVED Faculty of Science & Technology (until September 2018)
Depositing User: Lisa Blanshard
Date Deposited: 07 Feb 2020 12:16
Last Modified: 09 Sep 2021 16:10
URI: https://arro.anglia.ac.uk/id/eprint/705160

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