DataStories at SemEval-2017 Task 4: Deep LSTM with Attention for Message-level and Topic-based Sentiment Analysis

SEMEVAL 2017 Christos BaziotisNikos PelekisChristos Doulkeridis

In this paper we present two deep-learning systems that competed at SemEval-2017 Task 4 {``}Sentiment Analysis in Twitter{''}. We participated in all subtasks for English tweets, involving message-level and topic-based sentiment polarity classification and quantification... (read more)

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Evaluation Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK COMPARE
Sentiment Analysis SemEval Deep Bi-LSTM+attention F1-score 0.677 # 2