We present a comprehensive study on the emergence of Computational Social Science (CSS) - an interdisciplinary field leveraging computational methods to address social science questions - and its impact on adjacent social sciences. We trained a robust CSS classifier using papers from CSS-focused venues and applied it to 11 million papers spanning 1990 to 2021. Our analysis yielded three key findings. First, there were two critical inflections in the rise of CSS. The first occurred around 2005 when psychology, politics, and sociology began engaging with CSS. The second emerged in approximately 2014 when economics finally joined the trend. Sociology is currently the most engaged with CSS. Second, using the density of yearly knowledge embeddings constructed by advanced transformer models, we observed that CSS initially lacked a cohesive identity. From the early 2000s to 2014, however, it began to form a distinct cluster, creating boundaries between CSS and other social sciences, particularly in politics and sociology. After 2014, these boundaries faded, and CSS increasingly blended with the social sciences. Third, shared data-driven methods homogenized CSS papers across disciplines, with politics and economics showing the most alignment due to the combined influence of CSS and causal identification. Nevertheless, non-CSS papers in sociology, psychology, and politics became more divergent. Taken together, these findings highlight the dynamics of division and unity as new disciplines emerge within existing knowledge landscapes. A live demo of CSS evolution can be found in https://evolution-css.netlify.app/

翻译：我们针对计算社会科学的兴起及其对邻近社会科学领域的影响，开展了一项全面研究。计算社会科学是一个利用计算方法解决社会科学问题的交叉学科领域。我们使用专注于CSS的学术会议及期刊中的论文，训练了一个稳健的CSS分类器，并将其应用于1990年至2021年间跨度达1100万篇的论文。我们的分析得出了三个关键发现。首先，CSS的兴起存在两个关键转折点。第一个转折点出现在2005年左右，心理学、政治学和社会学开始涉足CSS。第二个转折点大约在2014年出现，经济学最终也加入了这一趋势。目前，社会学是与CSS结合最紧密的学科。其次，通过使用由先进Transformer模型构建的年度知识嵌入的密度进行分析，我们观察到CSS最初缺乏一个凝聚的学科身份。然而，从21世纪初到2014年，它开始形成一个独特的集群，在CSS与其他社会科学（尤其是政治学和社会学）之间建立了边界。2014年之后，这些边界逐渐淡化，CSS日益与社会科学相融合。第三，共享的数据驱动方法使得不同学科的CSS论文趋于同质化，其中政治学和经济学由于CSS与因果识别方法的共同影响而表现出最高的一致性。尽管如此，社会学、心理学和政治学中的非CSS论文却变得更加多样化。综上所述，这些发现揭示了在现有知识版图中，新学科兴起时所伴随的分裂与统一的动态过程。CSS演化的实时演示可在 https://evolution-css.netlify.app/ 查看。