Minions at SemEval-2016 Task 4: or how to build a sentiment analyzer using off-the-shelf resources?

SentimentalITsts at SemEval-2016 Task 4: building a Twitter sentiment analyzer in your backyard

Adullam at SemEval-2017 Task 4: Sentiment Analyzer Using Lexicon Integrated Convolutional Neural Networks with Attention

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…

\#WarTeam at SemEval-2017 Task 6: Using Neural Networks for Discovering Humorous Tweets

This paper presents the participation of {\#}WarTeam in Task 6 of SemEval2017 with a system classifying humor by comparing and ranking tweets. The training data consists of annotated tweets from the @midnight TV show. {\…

Strawman: an Ensemble of Deep Bag-of-Ngrams for Sentiment Analysis

This paper describes a builder entry, named "strawman", to the sentence-level sentiment analysis task of the "Build It, Break It" shared task of the First Workshop on Building Linguistically Generalizable NLP Systems. Th…

NileTMRG at SemEval-2017 Task 4: Arabic Sentiment Analysis

This paper describes two systems that were used by the authors for addressing Arabic Sentiment Analysis as part of SemEval-2017, task 4. The authors participated in three Arabic related subtasks which are: Subtask A (Mes…