Geoscope: Online detection of geo-correlated information trends in social networks

Ceren Budak, Theodore Georgiou, Divyakant Agrawal, Amr El Abbadi

Research output: Contribution to journalArticle

Abstract

The First Law of Geography states "Everything is related to everything else, but near things are more related than distant things". This spatial significance has implications in various applications, trend detection being one of them. In this paper we propose a new algorithmic tool, GeoScope, to detect geo-trends. GeoScope is a data streams solution that detects correlations between topics and locations in a sliding window, in addition to analyzing topics and locations independently. GeoScope offers theoretical guarantees for detecting all trending correlated pairs while requiring only sublinear space and running time. We perform various human validation tasks to demonstrate the value of GeoScope. The results show that human judges prefer GeoScope to the best performing baseline solution 4:1 in terms of the geographical significance of the presented information. As the Twitter analysis demonstrates, Geo- Scope successfully filters out topics without geo-intent and detects various local interests such as emergency events, political demonstrations or cultural events. Experiments on Twitter show that Geo- Scope has perfect recall and near-perfect precision.

Original languageEnglish
Pages (from-to)229-240
Number of pages12
JournalProceedings of the VLDB Endowment
Volume7
Issue number4
DOIs
Publication statusPublished - Dec 2013

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ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computer Science(all)

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