我国战略性新兴产业体系的政策文本分析——以通用航空产业为例

战略性新兴产业对于培育经济发展新动能、实现经济社会健康发展具有重要意义。以中央层面的通用航空产业政策文本为样本,从"政策工具-产业价值链"两个维度,采用政策文本分析法对政策条目进行量化分析,深入剖析我国通用航空产业政策中存在的政策工具使用不平衡、需求面政策工具缺失、产业价值链阶段政策不平衡等问题,并提出完善和优化我国通用航空产业政策的有关对策建议,包括适当降低供给面、环境面政策工具使用,兼顾需求面政策工具带动作用,以及重视政策工具在产业发展的全方位运用方面等,为完善我国战略性新兴产业相关政策提供参考。     

中国资源型城市研究20年回顾与展望

文章运用文献计量、供词分析等统计学方法,对CNKI中资源型城市相关研究进行统计分析。有关研究从20世纪90年代末以来经历探索期、研究激增期和波动下降期三个阶段,研究涉及领域逐渐从经济转向社会、生态等其他领域。结合资源型城市发展实践,研究主要集中于资源诅咒与资源型城市经济增长的关系、资源型城市转型和可持续发展等七个内容,它们都带有鲜明的经济和政策导向。为解决资源型城市可能面临的突出问题,预期资源诅咒与资源型城市经济增长的关系、资源型城市转型的道路选择等内容或将成为新的研究重点和核心内容。     

基于组合赋权和集对分析的施工项目绿色集成评价

随着建筑业对绿色环保和信息化水平的要求越来越高,传统的施工项目评价难以满足建筑业可持续发展的需要。文章利用扎根理论在传统评价的基础上,增加了绿色施工和信息化评价,构建8个维度的施工项目绿色评价指标体系;通过问卷调查和改进的群组G1赋权法对指标权重进行合理分配;最后结合集对分析计算指标等级联系度,建立面向施工项目的绿色评价模型,并通过工程实例验证了模型的有效性。     

区块链何去何从?——基于网络分析

区块链的发展正在逐步扩大,并收到国际上越来越多的关注与兴趣。本文提供了一个完整的文献计量和网络分析,使用了Web of Science的核心数据库,为区块链的发展提供了新的见解,并提高了覆盖面。首先确立了1633篇已经发表的文章,并使用文献计量学来提供研究领域的描述。接着进行网络分析,以确定有影响力的作者,有影响力的出版社,同时参考了h指数。通过Vosviewer进行可视化分析,研究4个集群的主题,更全面的内容分析确定了关键的研究领域。确定当前研究兴趣的领域和未来研究的潜在方向。     

基于DEMATEL专利模型的技术影响关系研究

技术间的相互影响、相互依存的关系推动着技术领域的发展和演变,开展专利技术交叉影响的探讨十分必要。目前,已有学者开展技术直接影响的研究,但技术间接影响的研究还较少,也较少考虑单个技术在技术体系中的关键程度和整体影响。本文提出一种基于DEMATEL模型的技术影响关系研究方法,可以识别技术间的直接影响关系和间接影响关系,还可以展示单个技术在技术体系中的位置和作用,从而全面了解专利技术间的交叉影响和内部结构。该方法有助于发现大量专利文献数据中有价值的技术模式或规则,理清技术的中心位置和相互影响,也有助于研发机构制定具有针对性的技术研发策略。基于地质建模专利的实证研究,证明了该方法在技术评估中的可行性和有效性。     

京津冀生态福利绩效及时空演变研究

京津冀协同发展是京津冀经济发展的新契机,但随着京津冀地区经济快速发展,对生态环境造成的巨大压力使得人们关注的重点逐渐从经济福利转向生态福利。本文运用熵权法-超效率SBM和空间相关分析,以京津冀13个地市为研究对象,测算2005-2017年区域生态福利绩效水平及空间相关性。研究发现：京津冀地区生态福利绩效水平大多数城市呈现波动上升最后趋于平稳态势。京津冀地区生态福利绩效水平在空间上呈现一定的相关性,观察分析2006、2010、2013及2017年莫兰散点图和LISA聚类变化图的变异,发现中心地市北京、保定、廊坊以及沧州主要形成高值聚集区;边缘地市邯郸、邢台、唐山和张家口组成低值聚集区,这就需要加强京津冀城市间经济生态福利协调发展。     

Social media opinion summarization using emotion cognition and convolutional neural networks

Quickly and accurately summarizing representative opinions is a key step for assessing microblog sentiments. The Ortony-Clore-Collins (OCC) model of emotion can offer a rule-based emotion export mechanism. In this paper, we propose an OCC model and a Convolutional Neural Network (CNN) based opinion summarization method for Chinese microblogging systems. We test the proposed method using real world microblog data. We then compare the accuracy of manual sentiment annotation to the accuracy using our OCC-based sentiment classification rule library. Experimental results from analyzing three real-world microblog datasets demonstrate the efficacy of our proposed method. Our study highlights the potential of combining emotion cognition with deep learning in sentiment analysis of social media data.     

A network-based concept extraction for managing customer requests in a social media care context

Web 2.0 changed everyday life in many aspects, including the whole system that orbits around the purchase of products and services. This revolution necessarily involved also companies, because customers became increasingly demanding. The diffusion of social media platforms pushed customers to prefer this channel for quickly obtaining information and feedback about what they want to buy, as well as for asking help after the selling. In this framework, many organisations adopted a new way of providing assistance known as social customer care. A direct link to companies allows customers to obtain real-time solutions. In this paper, we introduce a new strategy for automatically managing the information listed in the requests that customers send to the social media accounts of companies. Our proposal relies on the use of network techniques for extracting high-level structures from texts, highlighting the different concepts expressed into the customers’ written requests. The texts can be then organised on the basis of this new emerging information. An application to the requests sent to the AppleSupport service on Twitter shows the effectiveness of the strategy.     

Exploring CO2 mitigation pathway of local industries using a regional-based system dynamics model

Low-carbon development based on low energy consumption, low pollution and low emissions has become an important strategic choice for worldwide governments to achieve sustainable development. In order to support smart government in decision making, information systems have been developed to monitor and predict CO₂ emissions. Most of the existing studies investigate CO₂ emission amounts, identify influencing factors of CO₂ emission and discuss potential suggestions to mitigate CO₂ emission for different industries. They often focus on CO₂ emission research of industries in a region or country, while the integration of carbon flow in the neighboring regions is not well studied. Therefore, this paper proposes a system dynamics model to explore an optimal carbon emission reduction path of a regional industry by integrating regional differences, i.e., industrial comparative advantages, technology advantages and the inter-regional context between the neighboring regions. In the case study, we use a key industry in a typical industrial region of Western China, the cement industry in Chongqing, as a scenario to simulate the CO₂ emission, possible energy demand and cement production of the cement industry in this region for recent years. Simulation results show that by leveraging the regional differences, especially the collaboration of the industrial chain and production capacity among regions, the cement industry in Chongqing can achieve the low-carbon target. In addition, through the analysis and discussions about the features of our model and Chongqing’s cement industry, it reflects that our model using regional differences is applicable to industries with a common demand market at the regional level such as energy, chemical and steel industries.     

科技图书馆辅助高层次人才引进的服务案例研究

[目的/意义]探讨科技图书馆开展人才服务的方法和成效,为同行机构开展类似服务提供参考。[方法/过程]介绍广东省科技图书馆围绕高层次人才引进链条布局的服务链,并总结服务实践经验。[结果/结论]科技图书馆辅助高层次人才引进最关键要做好3点:一是要夯实数据基础,重视一手数据建设;二是要积极拓展业务面,重视工具方法组合创新;三是要综合多种服务模式,把握好时代热点和用户需求。