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A survey on location estimation techniques for events detected in Twitter

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Abstract

Detection of events using voluntarily generated content in microblogs has been the objective of numerous recent studies. One essential challenge tackled in these studies is estimating the locations of events. In this paper, we review the state-of-the-art location estimation techniques used in the localization of events detected in microblogs, particularly in Twitter, which is one of the most popular microblogging platforms worldwide. We analyze these techniques with respect to the targeted event type, granularity of estimated locations, location-related features selected as sources of spatial evidence, and the method used to make aggregate decisions based on the extracted evidence. We discuss the strengths and advantages of alternative solutions to various problems related to location estimation, as well as their preconditions and limitations. We examine the most widely used evaluation methods to analyze the accuracy of estimations and present the results reported in the literature. We also discuss our findings and highlight important research challenges that may need further attention.

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Notes

  1. https://dev.twitter.com/overview/api.

  2. http://www.geonames.org.

  3. https://developer.yahoo.com/boss/geo/.

  4. https://developers.google.com/maps/documentation/geocoding/intro.

  5. http://www.primefaces.org/.

  6. http://www.satscan.org/.

  7. http://twitterstand.umiacs.umd.edu.

  8. http://www.geovista.psu.edu/SensePlace2/.

  9. https://grait-dm.gatech.edu/demo-multi-source-integration/.

  10. https://sites.google.com/a/onailab.com/watanabe/jasmine.

  11. https://esa.csiro.au.

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Acknowledgements

This work was financially supported by TUBITAK with the Grant Number 112E275 and ICT COST Action IC1203.

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  1. Department of Computer Engineering, Middle East Technical University, Ankara, Turkey

    Ozer Ozdikis, Halit Oğuztüzün & Pinar Karagoz

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  1. Ozer Ozdikis
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Correspondence to Ozer Ozdikis.

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Ozdikis, O., Oğuztüzün, H. & Karagoz, P. A survey on location estimation techniques for events detected in Twitter. Knowl Inf Syst 52, 291–339 (2017). https://doi.org/10.1007/s10115-016-1007-z

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