|
Descripción
|
|
|---|---|
| This paper describes the `oeg' submission to task 1 of the TASS 2017 workshop, focusing on Sentiment Analysis at tweet level. different parameters and systems were tested in each one of the three corpora released for the task, including di erent Machine Learning algorithms and morphosyntactic analyses for negation detection, along with the use of lexicons and dedicated preprocessing techniques for detecting and correcting frequent errors and expressions in tweets. The obtained results o er a basis for the design of future strategies for systems to tackle Sentiment Analysis in Twitter. | |
|
Internacional
|
Si |
|
Nombre congreso
|
TASS 2017: Workshop on Sentiment Analysis |
|
Tipo de participación
|
960 |
|
Lugar del congreso
|
Murcia, España |
|
Revisores
|
Si |
|
ISBN o ISSN
|
1613-0073 |
|
DOI
|
|
|
Fecha inicio congreso
|
19/09/2017 |
|
Fecha fin congreso
|
19/09/2017 |
|
Desde la página
|
43 |
|
Hasta la página
|
49 |
|
Título de las actas
|
Proceedings of TASS 2017: Workshop on Sentiment Analysis at SEPLN co-located with 33nd SEPLN Conference (SEPLN 2017) http://ceur-ws.org/Vol-1896/ |