Name
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. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/s10115-016-1007-z | Knowl. Inf. Syst. |
Keywords | Field | DocType |
Location estimation, Event localization, Microblogs, Spatial analysis | Data mining,Social media,Event type,Computer science,Microblogging,Estimation,Granularity | Journal |
Volume | Issue | ISSN |
52 | 2 | 0219-3116 |
Citations | PageRank | References |
6 | 0.43 | 60 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Özer Özdikiş | 1 | 50 | 5.49 |
| Halit Oguztüzün | 2 | 208 | 26.40 |
| Pinar Karagoz | 3 | 154 | 28.34 |