Toponym recognition on Turkish tweets

Kezban Dilek Onal, Pinar Karagoz, Ruket Çakici

Abstract: In recent years, Twitter has become a popular platform for following and spreading trends, news and ideas all over the world. Geographical scope of tweets is crucial to many tasks like disaster management, event tracking and information retrieval. First step for assigning a geographical location to a tweet is toponym recognition. Toponym Recognition (Geoparsing) is identification of toponyms (place names) in a text. In this study, we investigated performance of three existing approaches for toponym recognition on Turkish tweets. We conducted experiments for measuring performance of the existing approaches on a sample data set. Best results have been obtained with the NER algorithm by Küçük et.al. However, we observed that existing NER algorithms for Turkish neglect the syntactic and semantic features of text.