Overview of NLPCC shared task 4: Stance detection in Chinese microblogs

Abstract

This paper presents the overview of the shared task, stance detection in Chinese microblogs, in NLPCC-ICCPOL 2016. The submitted systems are expected to automatically determine whether the author of a Chinese microblog is in favor of the given target, against the given target, or whether neither inference is likely. Different from regular evaluation tasks on sentiment analysis, the microblog text may or may not contain the target of interest, and the opinion expressed may or may not be towards to the target of interest. We designed two tasks. Task A is a mandatory supervised task which detects stance towards five targets of interest with given labeled data. Task B is an optional unsupervised task which gives only unlabeled data. Our shared task has had sixteen team participants for Task A and five results of Task B. The highest F-score obtained was 0.7106 for Task A and 0.4687 for Task B, respectively.