Abstract
This paper describes our approach to SemEval-2018 Task1: Estimation of Affects in Tweet for 1a and 2a. Our team KDE-AFFECT employs several methods including one-dimensional Convolutional Neural Network for n-grams, together with word embedding and other preprocessing such as vocabulary unification and Emoji conversion into four emotional words.- Anthology ID:
- S18-1022
- Volume:
- Proceedings of the 12th International Workshop on Semantic Evaluation
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans, Louisiana
- Venues:
- SemEval | *SEM
- SIGs:
- SIGLEX | SIGSEM
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 156–161
- Language:
- URL:
- https://aclanthology.org/S18-1022
- DOI:
- 10.18653/v1/S18-1022
- Cite (ACL):
- Masaki Aono and Shinnosuke Himeno. 2018. KDE-AFFECT at SemEval-2018 Task 1: Estimation of Affects in Tweet by Using Convolutional Neural Network for n-gram. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 156–161, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- KDE-AFFECT at SemEval-2018 Task 1: Estimation of Affects in Tweet by Using Convolutional Neural Network for n-gram (Aono & Himeno, SemEval-*SEM 2018)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/S18-1022.pdf