本文通过分析 Truth Social 上维基百科链接的传播，发现含链接的帖子互动更低、话题更中立，表明不应以政治标签一概而论地判定平台属性，而应深入考察具体内容。
摘要：
当前存在一种普遍看法，认为社交媒体平台上的内容通常具有相同的政治倾向。这些平台常被视为意识形态一致的实体，反映其多数用户的意见；Truth Social 就是一个典型例子。尽管这种看法可能存在，但仍有必要核实该平台的可信度，并承认此类平台也包含具有中立立场的有意义见解。为此，我们考察了维基百科链接在另类右翼平台 Truth Social 上的传播情况。维基百科以执行内容中立原则而著称，可作为分析 Truth Social 上用户生成内容客观性的独特视角。通过仔细审查带有和不带维基百科链接的 Truths、识别毒性趋势并识别协调网络，我们观察到，当 Truths 包含维基百科链接（Wiki Truths）时，其互动参与度较低，并且更倾向于涵盖更中立的话题。鉴于 Wiki Truths 与 Non-Wiki Truths 在互动参与度和内容性质上存在显著差异，我们强调不应一概而论地判定社交媒体平台的技术政治归属，而应深入调查其内容。
英文摘要：
There is a prevailing perception that content on a social media platform generally have the same political leaning. These platforms are often viewed as ideologically congruent entities, reflecting the majority opinion of their users; a prime example of this is Truth Social. While this perception may exist, it is essential to verify the platform's credibility, acknowledging that such platforms contain meaningful insights with neutral stances. To this end, we examine the dissemination of Wikipedia links on the alt-right platform, Truth Social. Wikipedia is recognized for enforcing content neutrality and serves as a unique lens to analyze the objectivity of user-generated content on Truth Social. By scrutinizing Truths with and without Wikipedia links, identifying toxicity trends & recognizing coordinated networks, we observe a lower level of engagement and a tendency for Truths shared on Truth Social to cover more neutral topics when it includes Wikipedia links (Wiki Truths). Given the significantly different engagement and nature of content shared of Wiki Truths against Non-Wiki Truths, we emphasize that we should not generalize the techno-political affiliation of a social media platform, but rather should investigate the content closely.
Against Political Polarization: A Unified Framework for Tracing Evolving Political Ideologies on Social Media
The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；University of Science and Technology of China（中国科学技术大学）；The Hong Kong University of Science and Technology（香港科技大学）
Grievance Politics vs. Policy Debates: A Cross-Platform Analysis of Conservative Discourse on Truth Social and Reddit
GESIS – Leibniz Institute for the Social Sciences（GESIS – 莱布尼茨社会科学研究所）；RWTH Aachen University（亚琛工业大学）；Heriot-Watt University（赫瑞-瓦特大学）；The University of Edinburgh（爱丁堡大学）；Massachusetts Institute of Technology（麻省理工学院）；Harvard University（哈佛大学）
Instilling Doubts About Truth: Measuring the Impact of Tucker Carlson's Interview with Vladimir Putin Using Machine Learning and Natural Language Processing
Leveraging Content Producer Networks and User Perception to Detect Online Discursive Communities
National Research Council of Italy, Institute for Applied Mathematics（意大利国家研究委员会应用数学研究所）；LUISS “Guido Carli” University（卢伊斯·圭多·卡尔利大学）；National Research Council of Italy, Institute of Complex Systems（意大利国家研究委员会复杂系统研究所）；Ca’ Foscari University of Venice（威尼斯卡福斯卡里大学）；London Institute for Mathematical Sciences（伦敦数学科学研究所）；“Enrico Fermi” Research Center（恩里科·费米研究中心）；IMT School for Advanced Studies Lucca（卢卡高等研究学院）
Community Moderation and the New Epistemology of Fact Checking on Social Media
University of Copenhagen（哥本哈根大学）；Massachusetts Institute of Technology（麻省理工学院）；Indian Institute of Technology Delhi（德里印度理工学院）；Full Fact（事实核查机构）；University of Southern California（南加州大学）；Technical University of Darmstadt（达姆施塔特技术大学）；University of Oxford（牛津大学）；The University of Melbourne（墨尔本大学）；University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；Newtrales（新特拉尔斯）；Indiana University（印第安纳大学）；EURECOM（EURECOM研究所）；Mohamed bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）；Pagella Politica/Facta
