We demonstrate the utility of a new methodological tool, neural-network word embedding models, for large-scale text analysis, revealing how these models produce richer insights into cultural associations and categories than possible with prior methods. Word embeddings represent semantic relations between words as geometric relationships between vectors in a high-dimensional space, operationalizing a relational model of meaning consistent with contemporary theories of identity and culture. We show that dimensions induced by word differences (e.g. man - woman, rich - poor, black - white, liberal - conservative) in these vector spaces closely correspond to dimensions of cultural meaning, and the projection of words onto these dimensions reflects widely shared cultural connotations when compared to surveyed responses and labeled historical data. We pilot a method for testing the stability of these associations, then demonstrate applications of word embeddings for macro-cultural investigation with a longitudinal analysis of the coevolution of gender and class associations in the United States over the 20th century and a comparative analysis of historic distinctions between markers of gender and class in the U.S. and Britain. We argue that the success of these high-dimensional models motivates a move towards "high-dimensional theorizing" of meanings, identities and cultural processes.
Seeing Symbols, Missing Cultures: Probing Vision-Language Models' Reasoning on Fire Imagery and Cultural Meaning
Duncan of Jordanstone College of Art & Design (DJCAD), University of Dundee（邓迪大学邓迪艺术与设计学院（DJCAD））；Guangzhou Institute of Science and Technology (GZIST)（广州科学技术研究院）；Faculty of Arts, Xiamen University（厦门大学艺术学院）；University of Birmingham（伯明翰大学）
From Words to Worlds: Benchmarking Cross-Cultural Cultural Understanding in Machine Translation
Xinjiang Technical Institute of Physics \& Chemistry, Chinese Academy of Sciences Urumqi China；Xinjiang Technical Institute of Physics \& Chemistry, Chinese Academy of Sciences
Many Dialects, Many Languages, One Cultural Lens: Evaluating Multilingual VLMs for Bengali Culture Understanding Across Historically Linked Languages and Regional Dialects
United International University（国际联合大学）；BRAC University（布拉塔克大学）；University of Maryland, Baltimore County（马里兰大学巴尔的摩县分校）
Are Expressions for Music Emotions the Same Across Cultures?
Max Planck Institute for Empirical Aesthetics（马克斯·普朗克实证美学研究所）；Max Planck Institute for Human Cognitive and Brain Sciences（马克斯·普朗克人类认知与脑科学研究所）；Cornell University（康奈尔大学）
From sunblock to softblock: Analyzing the correlates of neology in published writing and on social media
Vector Institute for Artificial Intelligence（向量人工智能研究所）；Carnegie Mellon University（卡内基梅隆大学）；The University of Texas at Austin（德克萨斯大学奥斯汀分校）；University of California, San Diego（加利福尼亚大学圣地亚哥分校）
The Differential Meaning of Models: A Framework for Analyzing the Structural Consequences of Semantic Modeling Decisions
Department of Computer Science and Engineering University of Central Arkansas（计算机科学与工程系美国中阿肯色大学）；Department of Philosophy and Religious Studies University of Central Arkansas（哲学与宗教研究系美国中阿肯色大学）
Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Study
Huazhong University of Science and Technology（华中科技大学）；University of Copenhagen（哥本哈根大学）；University of Electronic Science and Technology of China（电子科技大学）；Technical University of Darmstadt（达姆施塔特工业大学）；South China University of Technology（华南理工大学）
