Publicação
ej-sa-2017 at SemEval-2017 Task 4: Experiments for Target oriented Sentiment Analysis in Twitter
| Resumo: | This paper describes the system we have used for participating in Subtasks A (Message Polarity Classification) and B (Topic Based Message Polarity Classification according to a two-point scale) of SemEval2017 Task 4 Sentiment Analysis in Twitter. We used several features with a sentiment lexicon and NLP techniques, Maximum Entropy as a classifier for our system. |
|---|---|
| Autores principais: | Dovdon, Enkhzol |
| Outros Autores: | Saias, José |
| Assunto: | NLP Classification Opinion Mining Sentiment Analysis |
| Ano: | 2017 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade de Évora |
| Idioma: | inglês |
| Origem: | Repositório Científico da Universidade de Évora |
| Resumo: | This paper describes the system we have used for participating in Subtasks A (Message Polarity Classification) and B (Topic Based Message Polarity Classification according to a two-point scale) of SemEval2017 Task 4 Sentiment Analysis in Twitter. We used several features with a sentiment lexicon and NLP techniques, Maximum Entropy as a classifier for our system. |
|---|