DANTEStocks: A Multi-Layered Annotated Corpus of Stock Market Tweets for  Brazilian Portuguese

Ariani  Di-Felippo; Norton Trevisan Roman Roman

Autores/as

Ariani Di-Felippo Universidade Federal de São Carlos (UFSCar) | São Carlos | SP | BR https://orcid.org/0000-0002-4566-9352
Norton Trevisan Roman Roman Universidade de São Paulo (USP) São Paulo | SP | BR https://orcid.org/0000-0002-0563-2045

Palabras clave:

Brazilian Portuguese, stock market, Twitter, multi-layer annotation

Resumen

This paper introduces DANTEStocks, a pioneer multi-layered-annotated corpus for fostering research in Natural Language Processing (NLP) of user-generated content in Portuguese. Comprising 4,048 tweets (X posts) from the stock market domain written in Brazilian Portuguese, the corpus was annotated with three standoff layers of information, that is to wit, emotion categories (following Plutchik’s wheel of emotions); part-of-speech and dependency relations (under the Universal Dependencies framework); and named entities (according to the second HAREM’s taxonomy). The DANTEStocks corpus has been constructed within the context of the POeTiSA Project, which aims at increasing the amount of linguistic resources (lingwares) and fostering the development of tools and NLP applications for Brazilian Portuguese. In this article, we address the design of the several annotation tasks carried out in DANTEStocks, reporting on the available annotation results.

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Referencias

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