mib at SemEval-2016 Task 4a: Exploiting lexicon based features for Sentiment Analysis in Twitter

DL Team at SemEval-2018 Task 1: Tweet Affect Detection using Sentiment Lexicons and Embeddings

The paper describes our approach for SemEval-2018 Task 1: Affect Detection in Tweets. We perform experiments with manually compelled sentiment lexicons and word embeddings. We test their performance on twitter affect det…

IITPB at SemEval-2017 Task 5: Sentiment Prediction in Financial Text

This paper reports team IITPB{'}s participation in the SemEval 2017 Task 5 on {`}Fine-grained sentiment analysis on financial microblogs and news{'}. We developed 2 systems for the two tracks. One system was based on an …

IIT-TUDA at SemEval-2016 Task 5: Beyond Sentiment Lexicon: Combining Domain Dependency and Distributional Semantics Features for Aspect Based Sentiment Analysis

DUTH at SemEval-2017 Task 4: A Voting Classification Approach for Twitter Sentiment Analysis

This report describes our participation to SemEval-2017 Task 4: Sentiment Analysis in Twitter, specifically in subtasks A, B, and C. The approach for text sentiment classification is based on a Majority Vote scheme and c…

ARB-SEN at SemEval-2018 Task1: A New Set of Features for Enhancing the Sentiment Intensity Prediction in Arabic Tweets

This article describes our proposed Arabic Sentiment Analysis system named ARB-SEN. This system is designed for the International Workshop on Semantic Evaluation 2018 (SemEval-2018), Task1: Affect in Tweets. ARB-SEN prop…