论文标题
法律情绪分析和意见采矿（LSAOM）：自主AI法律推理的进步
Legal Sentiment Analysis and Opinion Mining (LSAOM): Assimilating Advances in Autonomous AI Legal Reasoning
论文作者
论文摘要
法律理论和法律惯例的扩展领域包括法律情绪分析和意见挖掘（LSAOM），由两个经常相互交织的现象和法律讨论和叙事的基础的行动组成：（1）在探索或暗示探索法律范围和（探索法律范围内的法律问题和（SA））和（SA）探索法律和（探索法律概念）和（2）分时（2）分析（2））或隐性意见伴奏融入法律话语中。从历史上看，进行LSAOM的努力是通过人的手和认知进行的，并且只有在最近的使用基于计算机的方法的情况下才能稀薄。涉及特别是自然语言处理（NLP）和机器学习（ML）的人工智能（AI）的进步正在越来越多地支持自动化如何系统地执行情感分析和意见挖掘的系统，所有这些都在不可避免地会涉及到提高LSAOM能力的合法环境中的互动。本研究论文研究了AI的不断发展到法律情绪分析和意见开采中，并提出与AI法律推理的自治水平（AILR）保持一致，Plus提供了有关AI LSAOM的其他见解，以及对法律研究和法律实践的潜在影响。
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.
