In this article we propose a stylistic analysis of texts written across two different periods, which differ not only temporally, but politically and culturally: communism and democracy in Romania. We aim to analyze the stylistic variation between texts written during these two periods, and determine at what levels the variation is more apparent (if any): at the stylistic level, at the topic level etc. We take a look at the stylistic profile of these texts comparatively, by performing clustering and classification experiments on the texts, using traditional authorship attribution methods and features. To confirm the stylistic variation is indeed an effect of the change in political and cultural environment, and not merely reflective of a natural change in the author's style with time, we look at various stylistic metrics over time and show that the change in style between the two periods is statistically significant. We also perform an analysis of the variation in topic between the two epochs, to compare with the variation at the style level. These analyses show that texts from the two periods can indeed be distinguished, both from the point of view of style and from that of semantic content (topic).
Towards Hybrid Intelligence in Journalism: Findings and Lessons Learnt from a Collaborative Analysis of Greek Political Rhetoric by ChatGPT and Humans
incubator for Media Education and Development (iMEdD)（媒体教育与发展孵化器（iMEdD））；School of Political Sciences, Aristotle University of Thessaloniki（塞萨洛尼基亚里士多德大学政治科学学院）；School of Informatics, Aristotle University of Thessaloniki（塞萨洛尼基亚里士多德大学信息学院）
ParlAI Vote: A Web Platform for Analyzing Gender and Political Bias in Large Language Models
Purdue University（普渡大学）；Johns Hopkins University（约翰霍普金斯大学）；Vanderbilt University（范德比大学）；University of Toronto（多伦多大学）；The University of Melbourne（墨尔本大学）
An Information-Theoretic Approach to Identifying Formulaic Clusters in Textual Data
Department of Statistics and Data Science, The Hebrew University of Jerusalem（统计与数据科学系，耶路撒冷希伯来大学）；Department of Statistics（统计系）；Data Science, The Hebrew University of Jerusalem（数据科学，耶路撒冷希伯来大学）；Faculty of Theology, Carl von Ossietzky Universität Oldenburg（神学系，卡尔·冯·奥西特齐克大学）
Are Economists Always More Introverted? Analyzing Consistency in Persona-Assigned LLMs
Research Centre for Information Systems Engineering (LIRIS), KU Leuven（信息系统工程研究中心（LIRIS），鲁汶大学）；Department of Engineering Management, University of Antwerp（工程管理系，安特卫普大学）；Department of Decision Analytics and Risk, University of Southampton（决策分析与风险系，南安普顿大学）；School of Information, University of Michigan（信息学院，密歇根大学）
Evaluating Large Language Models Against Human Annotators in Latent Content Analysis: Sentiment, Political Leaning, Emotional Intensity, and Sarcasm
Institute for Artificial Intelligence Research and Development of Serbia（塞尔维亚人工智能研究与发展研究所）；University of Belgrade（贝尔格莱德大学）；Institute for Philosophy and Social Theory（哲学与社会理论研究所）；Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau (RPTU)（莱茵兰-普法尔茨州 Kaiserslautern-Landau 应用科技大学）；German Research Centre for Artificial Intelligence (DFKI)（德国人工智能研究中心）；Vilnius Gediminas Technical University（维尔纽斯格迪米纳斯技术大学）；Drexel University（德雷塞尔大学）；University of Montenegro（黑山大学）；Faculty of Dramatic Arts（戏剧艺术学院）；University of Kragujevac（克拉古耶瓦茨大学）；Faculty of Engineering（工程学院）
