TY - GEN
T1 - Adullam at SemEval-2017 Task 4
T2 - 11th International Workshop on Semantic Evaluations, SemEval 2017, co-located with the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017
AU - Yoon, Joosung
AU - Lyu, Kigon
AU - Kim, Hyeoncheol
N1 - Funding Information:
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2017R1A2B4003558).
Publisher Copyright:
© 2017 Association for Computational Linguistics
PY - 2017
Y1 - 2017
N2 - We propose a sentiment analyzer for the prediction of document-level sentiments of English micro-blog messages from Twitter. The proposed method is based on lexicon integrated convolutional neural networks with attention (LCA). Its performance was evaluated using the datasets provided by SemEval competition (Task 4). The proposed sentiment analyzer obtained an average F1 of 55.2%, an average recall of 58.9% and an accuracy of 61.4%.
AB - We propose a sentiment analyzer for the prediction of document-level sentiments of English micro-blog messages from Twitter. The proposed method is based on lexicon integrated convolutional neural networks with attention (LCA). Its performance was evaluated using the datasets provided by SemEval competition (Task 4). The proposed sentiment analyzer obtained an average F1 of 55.2%, an average recall of 58.9% and an accuracy of 61.4%.
UR - http://www.scopus.com/inward/record.url?scp=85122577349&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85122577349
T3 - Proceedings of the Annual Meeting of the Association for Computational Linguistics
SP - 732
EP - 736
BT - ACL 2017 - 11th International Workshop on Semantic Evaluations, SemEval 2017, Proceedings of the Workshop
PB - Association for Computational Linguistics (ACL)
Y2 - 3 August 2017 through 4 August 2017
ER -