Social media platforms provide a goldmine for mining public opinion on issues of wide societal interest and impact. Opinion mining is a problem that can be operationalised by capturing and aggregating the stance of individual social media posts as supporting, opposing or being neutral towards the issue at hand. While most prior work in stance detection has investigated datasets that cover short periods of time, interest in investigating longitudinal datasets has recently increased. Evolving dynamics in linguistic and behavioural patterns observed in new data require adapting stance detection systems to deal with the changes. In this survey paper, we investigate the intersection between computational linguistics and the temporal evolution of human communication in digital media. We perform a critical review of emerging research considering dynamics, exploring different semantic and pragmatic factors that impact linguistic data in general, and stance in particular. We further discuss current directions in capturing stance dynamics in social media. We discuss the challenges encountered when dealing with stance dynamics, identify open challenges and discuss future directions in three key dimensions: utterance, context and influence.
Enhancing Stance Classification on Social Media Using Quantified Moral Foundations
School of Computing and Information Systems, Singapore Management University（新加坡管理大学计算与信息系统学院）；Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR)（新加坡科技研究局高性能计算研究所）；Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington（印第安纳大学伯明顿分校勒迪信息学、计算与工程学院）
Improved Target-specific Stance Detection on Social Media Platforms by Delving into Conversation Threads
Hong Kong Baptist University（香港浸会大学）；Nanjing University of Posts and Telecommunications（南京邮电大学）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；The University of Hong Kong（香港大学）
Discourse-Aware Rumour Stance Classification in Social Media Using Sequential Classifiers
University of Warwick（华威大学）；Alan Turing Institute（艾伦·图灵研究所）；University of Sheffield（谢菲尔德大学）；University of Melbourne（墨尔本大学）；University of Copenhagen（哥本哈根大学）
Clarifying Misconceptions in COVID-19 Vaccine Sentiment and Stance Analysis and Their Implications for Vaccine Hesitancy Mitigation: A Systematic Review
University of São Paulo（圣保罗大学）；University of Birmingham（伯明翰大学）；University of Rio de Janeiro State（里约热内卢州立大学）
Investigating Chain-of-thought with ChatGPT for Stance Detection on Social Media
College of Big Data and Internet, Shenzhen Technology University（深圳技术大学大数据与互联网学院）；Mohamed bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）；Shenzhen X-Institute（深圳X研究院）；Academy of Cyber, Beijing（北京网络研究院）
Optimizing Social Media Annotation of HPV Vaccine Skepticism and Misinformation Using Large Language Models: An Experimental Evaluation of In-Context Learning and Fine-Tuning Stance Detection Across Multiple Models
School of Journalism and Mass Communication, University of Wisconsin–Madison（威斯康星大学麦迪逊分校新闻与大众传播学院）；Department of Electrical & Computer Engineering, University of Wisconsin–Madison（威斯康星大学麦迪逊分校电气与计算机工程系）；Department of Computer Science, University of Wisconsin–Madison（威斯康星大学麦迪逊分校计算机科学系）；Department of Psychology, University of Wisconsin–Madison（威斯康星大学麦迪逊分校心理学系）；School of Interactive Computing, Georgia Institute of Technology（佐治亚理工学院交互计算学院）；Institute of People and Technology, Georgia Institute of Technology（佐治亚理工学院人与技术研究所）
Social media polarization during conflict: Insights from an ideological stance dataset on Israel-Palestine Reddit comments
Department of Business and Technology Management, Islamic University of Technology, Gazipur, Dhaka, Bangladesh（伊斯兰科技大学商学院与技术管理系，加兹ipur，达卡，孟加拉国）；Department of Computer Science and Engineering, Islamic University of Technology, Gazipur, Dhaka, Bangladesh（伊斯兰科技大学计算机科学与工程系，加兹ipur，达卡，孟加拉国）；Department of Electrical and Electronic Engineering, University of Dhaka, Nilkhet Road, Dhaka, Bangladesh（达卡大学电子与电气工程系，Nilkhet Road，达卡，孟加拉国）；Department of Computer Science, American International University–Bangladesh, Kuratoli, Dhaka, Bangladesh（孟加拉国美国国际大学计算机科学系，Kuratoli，达卡，孟加拉国）
Automated stance detection in complex topics and small languages: the challenging case of immigration in polarizing news media
School of Humanities, Tallinn University, Estonia（塔林大学人文学科学院，爱沙尼亚）；Baltic Film, Media and Arts School, Tallinn University, Estonia（巴尔蒂克电影、媒体与艺术学院，塔林大学，爱沙尼亚）；ERA Chair for Cultural Data Analytics, Tallinn University, Estonia（塔林大学文化数据分析埃拉教席，爱沙尼亚）
The Hong Kong University of Science and Technology（香港科技大学）；Carnegie Mellon University（卡内基梅隆大学）；University of California, Santa Barbara（加州大学圣巴巴拉分校）；University of Science and Technology of China（中国科学技术大学）
Contextualized Prompting For Stance Detection On Social Media
Institute of Intensive Care, University Hospital of Zurich and University of Zurich（重症医学研究所，苏黎世大学医院和苏黎世大学）；Institute of Computer Science, University of Goettingen（计算机科学研究所，哥廷根大学）；GESIS Leibniz Institute for the Social Sciences（社会科学研究莱比锡研究所）；Institut für Publizistik, Johannes Gutenberg-University Mainz（主笔研究所，美因茨约翰· Gutenberg 大学）；Ubiquitous Knowledge Processing Lab, Technical University of Darmstadt（无处不在知识处理实验室，达姆施塔特技术大学）
MT2-CSD: A New Dataset and Multi-Semantic Knowledge Fusion Method for Conversational Stance Detection
College of Big Data and Internet, Shenzhen Technology University（大数据与互联网学院，深圳技术大学）；University of Washington（华盛顿大学）；University of Science and Technology of China（中国科学技术大学）
What Media Frames Reveal About Stance: A Dataset and Study about Memes in Climate Change Discourse
MaiNLP & MCML, LMU Munich, Germany（LMU慕尼黑媒体与传播系）；Department of Media and Communication, LMU Munich, Germany（LMU慕尼黑媒体与传播系）；National Research Council Canada, Ottawa, Canada（加拿大国家研究委员会）
Semi-automatic Generation of Multilingual Datasets for Stance Detection in Twitter
Vicomtech Foundation（维康泰克基金会）；Basque Research and Technology Alliance (BRTA)（巴斯克研究与技术联盟（BRTA））；University of the Basque Country UPV/EHU（巴斯克大学（UPV/EHU））
Multi-modal Stance Detection: New Datasets and Model
Harbin Institute of Technology, Shenzhen（哈尔滨工业大学（深圳））；Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies（广东省新型安全智能技术重点实验室）；King’s College London（伦敦国王学院）；SIAT, Chinese Academy of Sciences（中国科学院深圳先进技术研究院）；Peng Cheng Laboratory（鹏城实验室）；The Chinese University of Hong Kong（香港中文大学）
A Challenge Dataset and Effective Models for Conversational Stance Detection
Shenzhen University（深圳大学）；Shenzhen Technology University（深圳技术大学）；Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences（中国科学院深圳先进技术研究院）；Harbin Institute of Technology, Shenzhen（哈尔滨工业大学（深圳））
SRLF: A Stance-aware Reinforcement Learning Framework for Content-based Rumor Detection on Social Media
Institute of Information Engineering, Chinese Academy of Sciences（中国科学院信息工程研究所）；School of Cyber Security, University of Chinese Academy of Sciences（中国科学院大学网络空间安全学院）
Zero-Shot Stance Detection in the Wild: Dynamic Target Generation and Multi-Target Adaptation
School of Information Engineering, Minzu University of China（中国民族大学信息工程学院）；National Language Resource Monitoring and Research Center of Minority Languages, Beijing（少数民族语言资源监测与研究中心）；Institute of National Security, Minzu University of China（中国民族大学国家安全学院）；School of Minority Languages and Literatures, Minzu University of China（中国民族大学少数民族语言文学学院）
