It has become a common pattern in our field: One group introduces a language task, exemplified by a dataset, which they argue is challenging enough to serve as a benchmark. They also provide a baseline model for it, which then soon is improved upon by other groups. Often, research efforts then move on, and the pattern repeats itself. What is typically left implicit is the argumentation for why this constitutes progress, and progress towards what. In this paper, we try to step back for a moment from this pattern and work out possible argumentations and their parts.
Assessing the Applicability of Natural Language Processing to Traditional Social Science Methodology: A Case Study in Identifying Strategic Signaling Patterns in Presidential Directives
Sentiment Analysis based Multi-person Multi-criteria Decision Making Methodology using Natural Language Processing and Deep Learning for Smarter Decision Aid. Case study of restaurant choice using TripAdvisor reviews
Andalusian Research Institute in Data Science and Computational Intelligence（安达卢西亚数据科学与计算智能研究所）；University of Granada（格拉纳达大学）
Data-to-Value: An Evaluation-First Methodology for Natural Language Projects
University of Zurich（苏黎世大学）；Thomson Reuters（汤森路透）；Essex University（埃塞克斯大学）；Coburg University of Applied Sciences（科堡应用科学大学）；University of Sheffield（谢菲尔德大学）
Efficiently Reusing Natural Language Processing Models for Phenotype-Mention Identification in Free-text Electronic Medical Records: Methodology Study
University of Edinburgh（爱丁堡大学）；Health Data Research（健康数据研究中心）；Nanjing University of Information Science & Technology（南京信息工程大学）；King’s College London（伦敦国王学院）；South London and Maudsley NHS Foundation Trust（南伦敦和莫兹利国民保健信托基金会）；The University of Melbourne（墨尔本大学）；Health Data Research UK（英国健康数据研究中心）；University College London（伦敦大学学院）
Audio-to-Score Conversion Model Based on Whisper methodology
College of Information Science and Engineering, East China University of Science and Technology（华东理工大学信息科学与工程学院）；School of Information and Software Engineering, University of Electronic Science and Technology of China（电子科技大学信息与软件工程学院）
Unraveling Media Perspectives: A Comprehensive Methodology Combining Large Language Models, Topic Modeling, Sentiment Analysis, and Ontology Learning to Analyse Media Bias
Institute of IT Management and Digitization Research (IFID)（信息管理与数字化研究学院）
