UAIC at SemEval-2019 Task 3: Extracting Much from Little

Cristian Simionescu, Ingrid Stoleru, Diana Lucaci, Gheorghe Balan, Iulian Bute, Adrian Iftene


Abstract
In this paper, we present a system description for implementing a sentiment analysis agent capable of interpreting the state of an interlocutor engaged in short three message conversations. We present the results and observations of our work and which parts could be further improved in the future.
Anthology ID:
S19-2062
Volume:
Proceedings of the 13th International Workshop on Semantic Evaluation
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota, USA
Editors:
Jonathan May, Ekaterina Shutova, Aurelie Herbelot, Xiaodan Zhu, Marianna Apidianaki, Saif M. Mohammad
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
355–359
Language:
URL:
https://aclanthology.org/S19-2062
DOI:
10.18653/v1/S19-2062
Bibkey:
Cite (ACL):
Cristian Simionescu, Ingrid Stoleru, Diana Lucaci, Gheorghe Balan, Iulian Bute, and Adrian Iftene. 2019. UAIC at SemEval-2019 Task 3: Extracting Much from Little. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 355–359, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
Cite (Informal):
UAIC at SemEval-2019 Task 3: Extracting Much from Little (Simionescu et al., SemEval 2019)
Copy Citation:
PDF:
https://aclanthology.org/S19-2062.pdf
Data
EmoContext