AI scientist systems are beginning to automate parts of scientific research, but social science poses a distinct challenge: its objects of inquiry are not merely datasets or laboratory protocols, but integrated social processes involving situated participants, interaction contexts, interventions, and outcomes. Yet a critical link is missing: existing systems either assist isolated research tasks or simulate agents as experimental subjects, leaving the research workflow and simulated society decoupled. Here we introduce AgentSociety 2, an Integrated Research Environment for executable social science. It couples two roles of LLM agents in the same runtime: AI social scientists that coordinate literature grounding, hypothesis generation, experiment design, simulation execution, result interpretation, and manuscript drafting; and silicon participants that generate behavioral responses within configurable social environments. This dual-role design turns hypotheses into auditable agent behaviors, environment rules, interventions, and measurements, thereby supporting an end-to-end workflow. Across seven illustrative studies spanning micro-level social-science laboratory experiments, meso-level dynamics in social media, and macro-level urban scenarios, we demonstrate its capacity to support diverse disciplinary questions, reproduce major qualitative patterns from prior studies, identify informative deviations, and enable large-scale simulations through optimized agent-environment interactions. By preserving human researchers' high-level agency while delegating procedural orchestration to agentic systems, it provides a human-in-the-loop and controllable infrastructure for next-generation computational social science, with broader applications in scalable computational social experimentation and AI-enabled social governance platforms.

Understanding human behavior and society is a central focus in social sciences, with the rise of generative social science marking a significant paradigmatic shift. By leveraging bottom-up simulations, it replaces costly and logistically challenging traditional experiments with scalable, replicable, and systematic computational approaches for studying complex social dynamics. Recent advances in large language models (LLMs) have further transformed this research paradigm, enabling the creation of human-like generative social agents and realistic simulacra of society. In this paper, we propose AgentSociety, a large-scale social simulator that integrates LLM-driven agents, a realistic societal environment, and a powerful large-scale simulation engine. Based on the proposed simulator, we generate social lives for over 10k agents, simulating their 5 million interactions both among agents and between agents and their environment. Furthermore, we explore the potential of AgentSociety as a testbed for computational social experiments, focusing on five key social issues: polarization, the spread of inflammatory messages, the effects of universal basic income policies, the impact of external shocks such as hurricanes, and urban sustainability. These five issues serve as valuable cases for assessing AgentSociety's support for typical research methods – such as surveys, interviews, and interventions – as well as for investigating the patterns, causes, and underlying mechanisms of social issues. The alignment between AgentSociety's outcomes and real-world experimental results not only demonstrates its ability to capture human behaviors and their underlying mechanisms, but also underscores its potential as an important platform for social scientists and policymakers.

This study seeks to advance our understanding of the role of nudges in fostering citizen co-production. We explore combinations of educative nudges-egoistic or altruistic information-and non-educative nudges-gain or loss frames-on citizens' co-production intentions. A survey experiment in a Chinese smart energy project showed individual nudges exhibit minimal impact, in contrast to the pronounced effectiveness of certain combinations, particularly gain frames with altruistic information and loss frames with egoistic information. These results underscore the nuanced dynamics of nudging in shaping citizens' intentions and stress the importance of strategically coherent policy designs that integrate multiple instruments to achieve greater efficacy in behavioral interventions. (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)"(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)"(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)((sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic))(sic)(sic)(sic)(sic)(sic)(sic)(sic)((sic)(sic)(sic)(sic)(sic)(sic)(sic))(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). Este estudio busca profundizar en nuestra comprensi & oacute;n del rol de los empujoncitos en el fomento de la coproducci & oacute;n ciudadana. Exploramos combinaciones de empujoncitos educativos (informaci & oacute;n ego & iacute;sta o altruista) y no educativos (marcos de ganancia o p & eacute;rdida) sobre las intenciones de coproducci & oacute;n de los ciudadanos. Un experimento de encuesta en un proyecto chino de energ & iacute;a inteligente mostr & oacute; que los empujoncitos individuales exhiben un impacto m & iacute;nimo, en contraste con la pronunciada efectividad de ciertas combinaciones, particularmente marcos de ganancia con informaci & oacute;n altruista y marcos de p & eacute;rdida con informaci & oacute;n ego & iacute;sta. Estos resultados subrayan la din & aacute;mica matizada del empujoncito en la configuraci & oacute;n de las intenciones ciudadanas y enfatizan la importancia de dise & ntilde;os de pol & iacute;ticas estrat & eacute;gicamente coherentes que integren m & uacute;ltiples instrumentos para lograr una mayor eficacia en las intervenciones conductuales.

Global efforts on feminism and women’s equality are undergoing intense challenges under the transformative impact of social media and artificial intelligence (AI). This study explores the polarization of public opinions on feminism—a prevalent yet underexplored phenomenon—by analyzing large-scale empirical data from one of China’s most prominent short video platforms. Facilitated by a fine-tuned large language model, we assess 62K users’ opinions on feminism based on their 67M fine-grained behavioral records over two years. We observe a severe polarization of opinions on feminism, where users are asymmetrically polarized into two opposing camps—54.3% in the conservative camp and 34.4% in the liberal camp. We further reveal that the AI-driven recommendation algorithm contributes to two primary drivers of this polarization: (i) echo chambers, where the algorithmic gathering of like-minded users reinforces their shared similar opinions and (ii) battlefields, where opposing users conflict, strengthening pre-existing opinions. We point out that these two drivers are asymmetrically applied to the polarized camps, with conservatives more prone to echo chambers while liberals are more inclined to battlefields. Our study not only uncovers the polarization of public opinions on feminism and its drivers but also offers implications for reducing polarization on increasingly AI-dependent social media.

It is necessary to analyse the technological innovation and market from the global level. We pay attention to the biopharmaceutical industry to study the relationship between them. We find all the technological innovation, market size, and market competitions are developing in increasing tendencies generally. But the tendencies change strongly when encountering major events. Market size is more effective than market competition when either one affects technological innovation. Market competition can only bring about slight innovations, but the market size can affect all kinds of innovations. Therefore, the best choice to develop technology is to expand its market, rather than to increase or decrease competition. However, the topic novelty and death still can only be resulted by global major events. At that time, the 'chance' should be seized, and cooperation should be emphasised on, since the urgent practical needs will accelerate the development of technology.

The Fukushima nuclear accident in Japan in 2011 substantially undermined global nuclear development, making public acceptance a particularly crucial influential factor worldwide. Although ample studies have identified factors shaping public acceptance, few researchers have paid attention to transitions in public acceptance and perception over the long term, and consistent observations of public acceptance across different periods of the same nuclear power plant (NPP) are particularly lacking. In this study we aim to fill this gap by exploring the transitions in public acceptance of a new NPP during construction phases including before licensing, during licensing, and during construction as well as differences in the influencing factors in each phase. We build up a unique dataset obtained from three rounds of surveys over 7 years in Huizhou City, China. The results reveal that public acceptance rises over time, and that underlying factors vary along with the development of NPPs and public relations campaigns at different phases. Perceived general benefits, government trust, and knowledge of a new local NPP continuously rise with public acceptance, and public perceived health risks continuously decrease over time. As a result, it is key for the government to understand the transition to public acceptance and perceptions of nuclear power and choose different communication strategies according to different phases.

Realizing the interconnection, interaction, and precise regulation of adjustable resources in the source network, load storage, is the key to expanding the control mode of the new power system and establishing flexible, reliable, and economical control methods. This article focuses on the demand for interactive response of adjustable resources in the source network load storage and provides the architecture of the interactive control system for the source network load storage interconnection, as well as the integration and management of adjustable load information. A decision scheduling method for large-scale adjustable resource demand response is proposed to support the interactive response and optimization control of multiple types of resources. Finally, the effectiveness of the proposed method was verified through case analysis.

智慧社区建设如何提升居民的社区认同是基层治理中的重要命题.选取北京两个老旧小区进行实地调查,探究智慧化改造影响居民社区依恋的机制.研究发现:社区智慧服务感知质量对社区依恋有正向作用,但其直接效应小于通过社会资本和居民满意度的间接效应;智慧社区建设中提高公众参与度、增加互动互信有助于提升社区依恋.

科技创新协同对于实现高质量研发、抢占产业高地具有重要意义.文章在静态、截面地理解科技创新协同的基础上,引入指向性动态视角,以粤港澳的跨制度科技创新协同为例,采用多案例比较的研究设计,梳理总结了科技创新协同中的指向性模式,基于政策计量描述了跨制度科技创新协同的现状,对政策要素、研发资金要素、产业要素、科研机构要素和人力资源要素与协同模式之间的关系做出 了描述性推论,并通过对比国际科创园建设实践,提出政策建议.研究发现,在缺乏科研机构要素和产业要素的情况下,研发资金的投入会导致自上而下的科技创新协同;在缺乏科研机构要素的情况下,产业要素和研发资金会激发自下而上的科技创新协同;而混合式科技创新协同则需要较为齐备的要素条件.

网络游戏对青少年成长影响的议题成为近几年"两会"的热点话题,也进一步引起学界的关注.为了更好地了解我国学者就此议题领域的研究现状以及发展态势,本文采用文献计量方法统计、分析网络游戏对青少年影响研究的学术论文的研究主题、理论基础与研究方法.研究发现,研究主题遵循从表象到本质、从宏观到微观、从广义到差异、从结果到原因的逻辑;理论基础从孤立运用技术社会学理论到交叉运用心理学、教育学、社会学、传播学等理论的演变逻辑;研究方法从单学科、多学科研究向交叉学科研究转变,并呈现出了从历史主义、规范主义向实证主义转变的趋势.在此基础上,提出对未来该议题研究的意见与建议.

Despite AI-driven recommendation algorithms being widely adopted to counter information overload, substantial evidence suggests that they are building cocoons of homogeneous contents and viewpoints, further aggravating social polarization and prejudice. Curbing these perils requires a deep insight into the origin of information cocoons. Here we investigate information cocoons in the real world using two large datasets and find that a large number of users are trapped in information cocoons. Further empirical analysis suggests that two ingredients, each corresponding to a fundamental mechanism in human–AI interaction systems, are correlated with the loss of information diversity. Grounded on the empirical findings, we derive a mechanistic model for the adaptive information dynamics in complex human–AI interaction systems governed by these fundamental mechanisms. It allows us to predict critical transitions between three states: diversification, partial information cocoons, and deep information cocoons. Our work not only empirically traces real-world information cocoons in two representative scenarios, but also theoretically unearths basic mechanisms governing the emergence of information cocoons. We provide a theoretical method for understanding major social issues resulting from adaptive information dynamics in complex human–AI interaction systems.

Responding to the impact of intelligent technological innovations,emerging self-organizations burgeon as the times require. Why are these types of self-organizations formed? What interactions with intelligent technologies have occurred? How are they different from self-organizations in traditional societies? These are theoretical propositions which urgently need to be answered. This paper examines the self-organization formed by takeaway riders（ food delivery drivers） and provides exploratory conclusions on the interaction between emerging self-organization and intelligent technology through field investigations. It supplements theoretical knowledge about self-organization and reveals empirically that takeaway riders may be trapped in the algorithm but they still have autonomy. These riders,based on introverted,interactive,or extroverted motivations,will eventually form self-organizations of physical,virtual, or coactive states through their organizational disengagement and virtual-identity-based connections. In the process of organizational development,riders will generate self-organizing adaptation through close and loose,direct and indirect interactions,sharing information resources,and forming self-organizing identities. Finally, the algorithm is fed back by takeaway riders through selforganization. This results in introverted algorithmic adaptation with self-persuasion, interactive algorithmic response with mutual adjustment,and extroverted algorithmic escape with external help. As this article argues,the government function of “guaranteeing the bottom line”for the emerging selforganizations in the context of intelligent technology can be achieved by broadening aggregation channels,providing pro bono legal aid,and guiding the direction of technological innovation.

伴随人工智能社会实验工作在全国的快速推进,学术界也围绕人工智能社会实验的基础理论与方法创新进行了深入研究,梳理了社会实验的基础理论、方法体系、数理分析模型、经典案例,形成了学术专著《社会实验理论与方法评介》.

地方政府大力引入移动政务服务是否助力"抢人大战",是中国城市高质量发展阶段值得研究的议题.基于新公共服务理论与人口迁移理论,匹配支付宝"城市服务"多源移动政务数据与中国流动人口动态监测调查数据,目的在于检验城市移动政务发展水平对增强城市流动人口定居意愿的影响.结果发现:移动政务发展水平越高,该城市流动人口定居意愿越强;控制个体特征、家庭随迁、地域流动等影响后,移动政务发展水平对流动人口定居意愿的促进作用仍然稳健;调节效应模型估计结果发现,年龄较大、已经购房、跨省流动、收入水平较高、教育水平较高的流动人口更容易感受到移动政务服务的便民性,从而提升定居意愿.研究成果在理论上有利于增进对移动政务对人口迁移作用机制的理解,在实践上有利于为政府或政策制定者通过智能技术进一步优化公共服务结构提供经验依据.

21世纪以来,我国网络游戏产业得到迅猛发展并成为了网络经济的重要增长点.与此同时,由于监管政策滞后等诸多原因,网络游戏又无异于"洪水猛兽",使很多青少年"玩物丧志".使用"中国教育追踪调查"2014年—2015年数据,探讨我国初中生玩游戏状况及其对教育期望的影响.研究发现,初中生玩网络游戏现象非常普遍;多层有序分类模型检验了玩游戏的强度对学生的教育期望存在的显著负向影响;分层模型检验了个体差异的调节效应,同伴辍学、学业成绩、亲子关系和学校分层强化了玩网络游戏对学生教育期望的负面影响,当同伴辍学人数越多、学业成绩和亲子关系越差、学校等级较低,其负面影响越强.此外,采用工具变量方法有效地解决了反向因果问题.由于学生自我教育期望是个体学业成就与国家人才培养体系的重要影响因素,玩游戏对教育期望的影响不容忽视.而出台合理的监管政策降低学生玩游戏时间,是新时代办好人民满意的教育的亟需措施.

Industry-university collaboration（IUC）has become an important element for the innovation-driven development strategy and transformation of scientific and technological achievements in China. With the continuous development of IUC, more and more innovative enterprises and research universities join in the technology collaboration through resource share and complement of each other’s advantages, which form the IUC networks with multiplex actors,abundant relationships and complex structure. A part of present literature on IUC network focuses on the descriptive analysis of collaboration mode and identification of the key actors, and the other literature explores its effect on innovation outcomes. There is a lack of discussion on the dynamic mechanism of IUC network. Therefore, combining with network system dynamics,this paper explores the formation mechanism of IUC network from the technical, social and geographical dimensions.This paper takes IUC of Chinese artificial intelligence technology as a case. We measure the key indicators and construct IUC network based on the patent data of Chinese artificial intelligence technology. Specifically, this paper uses the information of patentee and international patent classification from 2000 to 2019 to measure the independent variables:three technical factors including technological diversity, technological value and technological similarity, social factors represented by structural embeddedness, geographical factors represented by geographical proximity. The IUC network was constructed using the patentee information from 2020 to2021 as the dependent variable of this study. Finally, the Exponential Random Graph Model（ERGM）is adopted to analyze the influence of above mentioned endogenous and exogenous factors on the evolution of IUC network. The analysis tool is software Pnet.The empirical results show that diverse technology base and similar technology background will promote universities and enterprises to join the IUC network. The results also indicate that universities with higher technological value are more likely to be selected as partners by enterprises. In addition, the IUC network shows an inverse core-marginal trend, i.e. the universities and enterprises will choose a small number of partners for in-depth collaboration. Finally, the positive results of geographical proximity show that the IUC is more likely to occur within the province area. Our research results enrich the theories related to the evolution of the IUC network and provide ideas and scientific basis for the government to guide and promote the IUC in an orderly manner.

Policy documents have become increasingly valuable in the field of bibliometrics because they contain important information such as the intentions and behaviors of policymakers. Policy instruments are the central elements of policy documents; therefore, identifying core policy instruments can help researchers in the field better understand the important methodological measures taken by government organizations to achieve specific economic or social goals. However, existing identification methods often focus on the effectiveness of a policy instrument along one dimension (e.g., economic indicators), while ignoring the relationship between individual policy instruments. This paper attempts to fill this gap by designing a network-based framework incorporating structural holes theory to identify the core policy instruments implied in the policy documents. We first identify "policy target-policy instrument" patterns in relevant policy documents and then establish a "policy target-policy instrument" network that maps onto real -world policy systems. Finally, using structural holes theory, we identify core policy instruments and analyze the policy mix system upon this basis. We use China's nuclear energy policy as a case study to evaluate the proposed approach. Our proposed method is useful for quantitatively analyzing complex policy systems and for identifying core policy instruments and targets within them. (C) 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://Creativecommons.org/licenses/by-nc-nd/4.0/).

The purpose of this study is to explore the characteristics of local government's reputation management in response to public protests under the dual pressure from higher-level authorities and the public. This study connects reputation management theory to the literature on local governments in the dual pressure dilemma. By comparing three cases of how local governments respond to public protests against nuclear facilities in China, we conclude that different pressures perceived by local governments generate diverse behaviours of reputation management in response to public protests. If the perceived bottom-up pressure is higher, local governments will focus on their moral reputation and make concessions to the public; if the perceived top-down pressure is higher, local governments will build a performative reputation to meet the demands of higher-level authorities and suppress public protests; if local governments face dual high pressures, they will comply with all normative procedures and avoid accountability to any party.