标题： 法律情感分析与意见挖掘（LSAOM）：融合自主人工智能法律推理的进展 显示英文标题

标题： Legal Sentiment Analysis and Opinion Mining (LSAOM): Assimilating Advances in Autonomous AI Legal Reasoning

摘要： 一个具有实质性兴趣的新兴领域是法律理论和法律实践中的法律情感分析与观点挖掘（LSAOM），它包括两种常常交织的现象和行为，这些现象和行为是法律讨论和叙述的基础：（1）情感分析（SA），用于检测法律环境中关于法律事务所表达或隐含的情感，以及（2）观点挖掘（OM），用于识别和阐明嵌入在法律话语中的显性或隐性观点伴随之物。 以往进行LSAOM的努力一直是由人工完成的，仅在最近才通过使用基于计算机的方法得到少量辅助。 涉及自然语言处理（NLP）和机器学习（ML）的人工智能（AI）方面的进步正在日益增强自动化系统能够系统地执行情感分析和观点挖掘中的一个或两个方面，所有这些都不可避免地被引入法律情境中以提高LSAOM的能力。 本文研究论文考察了人工智能在法律情感分析和观点挖掘中的不断融入，并提出了与人工智能法律推理（AILR）的自主水平（LoA）相一致的观点，同时还提供了关于人工智能LSAOM在机械化及其对法律研究和法律实践潜在影响方面的额外见解。 显示英文摘要

摘要： An expanding field of substantive interest for the theory of the law and the practice-of-law entails Legal Sentiment Analysis and Opinion Mining (LSAOM), consisting of two often intertwined phenomena and actions underlying legal discussions and narratives: (1) Sentiment Analysis (SA) for the detection of expressed or implied sentiment about a legal matter within the context of a legal milieu, and (2) Opinion Mining (OM) for the identification and illumination of explicit or implicit opinion accompaniments immersed within legal discourse. Efforts to undertake LSAOM have historically been performed by human hand and cognition, and only thinly aided in more recent times by the use of computer-based approaches. Advances in Artificial Intelligence (AI) involving especially Natural Language Processing (NLP) and Machine Learning (ML) are increasingly bolstering how automation can systematically perform either or both of Sentiment Analysis and Opinion Mining, all of which is being inexorably carried over into engagement within a legal context for improving LSAOM capabilities. This research paper examines the evolving infusion of AI into Legal Sentiment Analysis and Opinion Mining and proposes an alignment with the Levels of Autonomy (LoA) of AI Legal Reasoning (AILR), plus provides additional insights regarding AI LSAOM in its mechanizations and potential impact to the study of law and the practicing of law.