Add to ORKGInternational audienceThis paper presents the contribution of our team at task 2 of SemEval 2013: Sentiment Analysis in Twitter. We submitted a constrained run for each of the two subtasks. In the Contextual Polarity Disambiguation subtask, we use a sentiment lexicon approach combined with polarity shift detection and tree kernel based classifiers. In the Message Polarity Classification subtask, we focus on the influence of domain information on sentiment classification
Social media analytics tool aims at eliciting information and knowledge about individuals and commun...
Social media analytics tool aims at eliciting information and knowledge about individuals and commun...
Twitter is a medium that we can use for communication. All posted tweets we can store in one locatio...
International audienceThis paper presents the contribution of our team at task 2 of SemEval 2013: Se...
This paper presents the approach of the CISUC-KIS team to the SemEval 2014 task on Sentiment Analysi...
This paper describes our participation at SemEval-2014 sentiment analysis task, in both contextual a...
With the objective of extracting useful information from the vast amount of opinion-rich data on Twi...
This paper describes our contribution to the SemEval-2014 Task 9 on sentiment analysis in Twitter. W...
We present a sentiment classification sys-tem that participated in the SemEval 2014 shared task on s...
Microblogs are considered as We-Media infor-mation with many real-time opinions. This paper presents...
This work presents our team solution for task 4a (Message Polarity Classification) at the SemEval 20...
This study focuses on automatic extraction of sentiment expressions associated with given targets fr...
This paper describes the system we have used for participating in Subtasks A (Message Polarity Class...
In this study we explore a novel technique for creation of polarity lexicons from the Twitter stream...
International audienceWe present, in this paper, our contribution in SemEval2017 task 4 : " Sentimen...
Social media analytics tool aims at eliciting information and knowledge about individuals and commun...
Social media analytics tool aims at eliciting information and knowledge about individuals and commun...
Twitter is a medium that we can use for communication. All posted tweets we can store in one locatio...
International audienceThis paper presents the contribution of our team at task 2 of SemEval 2013: Se...
This paper presents the approach of the CISUC-KIS team to the SemEval 2014 task on Sentiment Analysi...
This paper describes our participation at SemEval-2014 sentiment analysis task, in both contextual a...
With the objective of extracting useful information from the vast amount of opinion-rich data on Twi...
This paper describes our contribution to the SemEval-2014 Task 9 on sentiment analysis in Twitter. W...
We present a sentiment classification sys-tem that participated in the SemEval 2014 shared task on s...
Microblogs are considered as We-Media infor-mation with many real-time opinions. This paper presents...
This work presents our team solution for task 4a (Message Polarity Classification) at the SemEval 20...
This study focuses on automatic extraction of sentiment expressions associated with given targets fr...
This paper describes the system we have used for participating in Subtasks A (Message Polarity Class...
In this study we explore a novel technique for creation of polarity lexicons from the Twitter stream...
International audienceWe present, in this paper, our contribution in SemEval2017 task 4 : " Sentimen...
Social media analytics tool aims at eliciting information and knowledge about individuals and commun...
Social media analytics tool aims at eliciting information and knowledge about individuals and commun...
Twitter is a medium that we can use for communication. All posted tweets we can store in one locatio...