You can view the full text of this article for free using the link below.

Title: Exploratory pattern mining on social media using geo-references and social tagging information

Authors: Martin Atzmueller; Florian Lemmerich

Addresses: Knowledge and Data Engineering Group, University of Kassel, Wilhelmshöher Allee 73, 34121 Kassel, Germany ' Artificial Intelligence and Applied Computer Science Group, University of Würzburg, Am Hubland, 97074 Würzburg, Germany

Abstract: This paper presents exploratory pattern mining techniques for describing communities of resources (e.g., images) and for characterising locations of interest. We utilise tagging information and collaborative geo-reference annotations for characterising resources locations by a set of descriptive patterns. The methods are embedded into an interactive approach for mining, browsing and visualising a set of patterns. As an exemplary use case, we focus on the social photo sharing application Flickr. Utilising publicly available real-world data from this platform, we provide a structural evaluation of the automatic approach as well as an exemplary case study for demonstrating the effectiveness and validity of the interactive approach.

Keywords: social web; social media; community detection; pattern mining; geospatial analysis; web science; geo-references; social tagging information; communities of resources; locations of interest; geo-reference annotations; resource location; social photo sharing; Flickr.

DOI: 10.1504/IJWS.2013.056577

International Journal of Web Science, 2013 Vol.2 No.1/2, pp.80 - 112

Available online: 25 Sep 2013 *

Full-text access for editors Access for subscribers Free access Comment on this article