Stance detection on social media is an emerging opinion mining paradigm for various social and political applications wheresentiment analysis might be seen sub-optimal. This paper surveys the work on stance detection and situates its usage withincurrent opinion mining techniques in social media. An exhaustive review of stance detection techniques on social media ispresented, including the task definition, the different types of targets in stance detection, the features set used, and the variousmachine learning approaches applied. The survey reports the state-of-the-art results on the existing benchmark datasets onstance detection, and discusses the most effective approaches.In addition, this study explores the emerging trends and the different applications of stance detection on social media.The study concludes by providing discussion of the gabs in the current existing research and highlighting the possible futuredirections for stance detection on social media

该文综述了社交媒体上基于观点挖掘的新兴姿态检测技术，比较了不同领域的方法，包括自然语言处理、Web科学和社交计算，并在现有基准数据集上介绍了这些姿态检测技术的最新结果，讨论了最有效的方法和技术，还探讨了社交媒体上姿态检测的新趋势和应用，最后总结了目前该领域存在的缺陷和未来发展方向。

社交媒体立场检测：现状与趋势