Gaillat, Thomas, Zarrouk, Manel, Freitas, Andre and Davis, Brian (2018) The SSIX Corpora: Three Gold Standard Corpora for Sentiment Analysis in English, Spanish and German Financial Microblogs. In: LREC 2018, Eleventh International Conference on Language Resources and Evaluation. European Language Resources Association, pp. 2671-2675. ISBN 9791095546009
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Abstract
This paper introduces the three SSIX corpora for sentiment analysis. These corpora address the need to provide annotated data for
supervised learning methods. They focus on stock-market related messages extracted from two financial microblog platforms, i.e.,
StockTwits and Twitter. In total they include 2,886 messages with opinion targets. These messages are provided with polarity annotation
set on a continuous scale by three or four experts in each language. The annotation information identifies the targets with a sentiment
score. The annotation process includes manual annotation verified and consolidated by financial experts. The creation of the annotated
corpora took into account principled sampling strategies as well as inter-annotator agreement before consolidation in order to maximize
data quality.
Item Type: | Book Section |
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Additional Information: | The LREC 2018 Proceedings are licensed under a Creative Commons Attribution-NonCommercial 4.0 International License https://creativecommons.org/licenses/by-nc/4.0/ We would like to thank all the people involved in the creation of the Gold Standard. This work is funded by the SSIX Horizon 2020 project (Grant agreement No 645425) |
Keywords: | Sentiment Analysis; Opinion; Corpus; Finance; Stock-market; Microblogs; Polarity Annotation; |
Academic Unit: | Faculty of Science and Engineering > Computer Science |
Item ID: | 13418 |
Depositing User: | Brian Davis |
Date Deposited: | 07 Oct 2020 15:09 |
Publisher: | European Language Resources Association |
Refereed: | Yes |
Funders: | European Union Horizon 2020 programme |
Related URLs: | |
URI: | https://mural.maynoothuniversity.ie/id/eprint/13418 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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