Abstract
Over the past few years the web has experienced an exponential growth in the use of weblogs or blogs, web sites containing journal-style entries presented in reverse chronological order. In this paper we provide an analysis of the type of recommendation strategy suitable for this domain. We introduce measures to characterise the blogosphere in terms of blogger and topic drift and we demonstrate how these measures can be used to construct a plausible explanation for blogger behaviour. We show that the blog domain is characterised by bloggers moving frequently from topic to topic and that blogger activity closely tracks events in the real world. We then demonstrate how tag cloud information within each cluster allows us to identify the most topic-relevant and consistent blogs in each cluster. We briefly describe how we plan to integrate this work within the SIOC framework.
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Hayes, C., Avesani, P., Bojars, U. (2007). An Analysis of Bloggers, Topics and Tags for a Blog Recommender System. In: Berendt, B., Hotho, A., Mladenic, D., Semeraro, G. (eds) From Web to Social Web: Discovering and Deploying User and Content Profiles. WebMine 2006. Lecture Notes in Computer Science(), vol 4737. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74951-6_1
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DOI: https://doi.org/10.1007/978-3-540-74951-6_1
Publisher Name: Springer, Berlin, Heidelberg
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