Geotagging Twitter Messages in Crisis Management.
During times of crisis microblogging platforms such as Twitter have played an important role as a communication channel to distribute information. Particularly, disaster-related tweets are valuable resources when tagged with their location for detecting unexpected events. However, they often contain different types of location and one of the main challenges is resolving the ambiguity involved in their locations. The process of identifying phrase portions in unstructured texts with possible spatial aspects and disambiguating these references by linking them to geographic coordinates is known as Geotagging. In the context of crisis management, this paper presents OzCT geotagger that automatically detects the location(s) mentioned in the content of tweets with three possibilities: definite, ambiguous and no-location. It also semantically annotates the tweet components utilizing existing and new ontologies. The OzCT geotagger has been recently deployed in a trial system of the OzCrisisTracker application. Experiments demonstrate that the precision and recall for detection of the definite locations against geotagging by human judgement are on average of 80%. We also conclude that the accuracy of geographical focus of the OzCT geotagger is considerably higher than other systems. While existing geocoding systems have lower coverage for suburb and street focus, our approach detects suburbs in more than 60% situations. [ABSTRACT FROM AUTHOR]/nCopyright of Computer Journal is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Comparison against manual human geotagging, existing solutions, existing data sets.
Literature review, tool development, evaluation
Software developmentFirst, we evaluated the system by comparing its output against human judgement as ground truth for a selection of 500 tweetsSecondly, we tested our geotagger performance with the testing dataset against other geocoding platforms including: The Alchemy API NER and the Yahoo! GeoPlanet service.The IBM research (Australia) plans the OzCrsisTracker 2.0 deployment in the Australian Bushfire and Flood season 2014.
he OzCT geotagger has been recently deployed in a trial system of the OzCrisisTracker application.The best method to evaluate the effectiveness of automated or semi-automated geotagging processes—such as identifying geo/non-geo references, specifying the geographic focus in the content and disambiguation of the results of the geo references—is to compare the results with manual human geotagging.
In addition, data resources such as Flickr, Facebook and Youtube as the feeder for OzCrisisTracker 2.0 will also take into account and the OzCT geotagger is expected to geotag such complex multimedia messages with some further development in analysing multimedia messageswe believe that presented semantic annotation of tweets in this research that utilizes existing and new ontologies, can be used for conceptual analysis of tweets content and will resolve the ambiguity of tweet locations to significantly improve the geotagger performance
Experiments demonstrate that the precision and recall for detection of the definite locations against geotagging by human judgement are on average of 80%. We also conclude that the accuracy of geographical focus of the OzCT geotagger is considerably higher than other systems. While existing geocoding systems have lower coverage for suburb and street focus, our approach detects suburbs in more than 60% situations.
this paper presents OzCT geotagger that automatically detects the location(s) mentioned in the content of tweets with three possibilities: definite, ambiguous and no-location.It also semantically annotates the tweet components utilizing existing and new ontologies.
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Portfolio of Solutions web site has been initially developed in the scope of DRIVER+ project. Today, the service is managed by AIT Austrian Institute of Technology GmbH., for the benefit of the European Crisis Management. PoS is endorsed and supported by the Disaster Competence Network Austria (DCNA) as well as by the STAMINA and TeamAware H2020 projects. |