讲 座 信 息

主题：CSS learns from STS

时间：2024年10月25日（周五）13:30-15:30

地点：浙江大学紫金港西区成均苑8幢1017

摘要：The influx of Natural Language Processing (NLP) technologies from the technology sector into academia has catalyzed the expansion of computational social science in the last decade. However, the significant contrasts in the political-economic regimes between these domains have been largely overlooked by researchers. Algorithms commonly deployed in both spheres perform divergently, yielding variable outcomes due to the disparate roles they fulfill in the technology industry versus academic research. Our study focuses on topic modeling, a popular NLP technique in computational social science, to illustrate this gap. Social scientists grapple with the algorithmic instability when applied to identical corpus—a non-issue for tech industry professionals. To understand this discrepancy, we conducted a historical genealogical analysis of topic modeling’s development and its diffusion from industry to social science. Our findings reveal that identical algorithms, when situated in distinct organizational settings and aimed at different objectives, are subject to alternative evaluative standards. In short, the governing political-economic regimes of it are different in these two domains. Reflecting on these findings, we propose that methodological transfers in technology are not merely technical in nature. Algorithms and their application have political and economic presuppositions. In this sense, computational social science has many to learn from digital sociology and critical algorithm studies.

主讲人：张博伦，浙江大学社会学系百人计划研究员

加州大学圣迭戈分校博士，研究兴趣包括数字社会学、经济社会学、物质政治经济学等。特别关注技术系统、专家知识等基础设施是如何同政治经济体制互动，这种互动又怎么扩展了我们对于“政治”的认识。在这个理论目标下，其研究既关注信息产业的发展，也关注信息产业的算法技术进入社会学后产生的各种后果。相关的研究发表在BigData and Society, 清华社会学评论上，进行中的工作正在Sociological Methodology和World Development等期刊上接受匿名评审中。

评议人：李林倬，浙江大学社会学系百人计划研究员

芝加哥大学社会学博士，研究领域为知识社会学、计算社会科学、经济社会学。研究方向为知识系统和经济系统中的创新、颠覆、不确定性和层级相关的议题。研究发表在Poetics, Plos One, npj Urban Sustainability, 和社会学研究等中英文期刊上。

主持人：戴良灏，浙江大学社会学系百人计划研究员

哥廷根大学社会学博士，研究领域包括科学社会学，科学与技术研究（STS），社会网理论，认知图等。当下重点关注科学知识生产过程中的跨学科合作问题和学术劳动问题。相关研究论文和报告发表在Nature，Natureindex，ACM-KDD，EASST Review，Social Network Analysis: Interdisciplinary Approaches and Case Studies等刊著上。