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| An empirical evaluation of electronic annotation tools for Twitter data |
| Davy Weissenbacher, Karen O'Connor, Aiko T. Hiraki, Jin-Dong Kim, Graciela Gonzalez-Hernandez |
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Genomics Inform. 2020;18(2):e24 Published online June 17, 2020 DOI: https://doi.org/10.5808/GI.2020.18.2.e24 |
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An empirical evaluation of electronic annotation tools for Twitter data Genomics & Informatics. 2020;18(2):e24  Sentiment analysis of multimodal twitter data Multimedia Tools and Applications. 2019;78(17):24103-24119 Signal detection in pharmacovigilance: empirical evaluation of data mining tools Pharmacoepidemiology and Drug Safety. 2005;14(9):597-599 Tools for Multimodal Annotation Handbook of Linguistic Annotation. 2017;209-227 RDF-powered semantic video annotation tools with concept mapping to Linked Data for next-generation video indexing: a comprehensive review Multimedia Tools and Applications. 2016;76(12):14437-14460 Confidence Levels for Empirical Research Using Twitter Data Proceedings of the Technology, Mind, and Society. 2018; Ground truth annotation of traffic video data Multimedia Tools and Applications. 2013;70(1):461-474 Editorial preface: special issue on multimedia data annotation and retrieval using web 2.0 Multimedia Tools and Applications. 2012;64(1):1-5 Field- and time-normalization of data with many zeros: an empirical analysis using citation and Twitter data Scientometrics. 2018;116(2):997-1012 Overview of Annotation Creation: Processes and Tools Handbook of Linguistic Annotation. 2017;167-191 |
