JU_NLP at SemEval-2016 Task 6: Detecting Stance in Tweets using Support Vector Machines
Braja Gopal Patra, Dipankar Das, Sivaji Bandyopadhyay · 2016
We describe the system submitted to the SemEval-2016 for detecting stance in tweets (Task 6, Subtask A).One of the main goals of stance detection is to automatically determine the stance of a tweet towards a specific target as 'FAVOR', 'AGAINST', or 'NONE'.We developed a supervised system using Support Vector Machines to identify the stance by analyzing various lexical and semantic features.The average F1 score achieved by our system is 60.60.