网络舆情衍进指数构建与实证分析   总被引：1，自引：0，他引：1  

黄微  朱镇远  许烨婧  孙悦 《图书情报工作》2019,63(20):26-33

[目的/意义]提出和构建网络舆情衍进指数，以描述网络舆情演化过程中常衍生出新的子话题的现象，对于舆情预警、预测具有重要的理论及实践意义。[方法/过程]以文本聚类结果和文本聚类有效性为依据，提出网络舆情衍进的判别标准和舆情衍进指数的构建过程，并以"教科书老赖"这一事件作为样本数据进行实证分析。[结果/结论]所构建的舆情衍进速率指数可以用于描述舆情衍进。在突发期阶段话题舆情衍进指数最高，此后逐渐下降，这一阶段的舆情衍进最为剧烈，子话题的出现呈现爆发性增长；舆情衍进指数在舆情蔓延期内出现阶梯式下降，此后保持为负值，舆情的子话题开始逐渐减少，舆情内容本身由发散转为收敛；进入消散期后，子话题数量趋于稳定。作为舆情衍进速率的测度和舆情衍进的判别方式，舆情衍进指数为舆情监管和舆情预警提供了全新的角度。  相似文献   

Understanding the topic evolution of scientific literatures like an evolving city: Using Google Word2Vec model and spatial autocorrelation analysis     

Kai Hu  Qing Luo  Kunlun Qi  Siluo Yang  Jin Mao  Xiaokang Fu  Jie Zheng  Huayi Wu  Ya Guo  Qibing Zhu 《Information processing & management》2019,56(4):1185-1203

Topic evolution has been described by many approaches from a macro level to a detail level, by extracting topic dynamics from text in literature and other media types. However, why the evolution happens is less studied. In this paper, we focus on whether and how the keyword semantics can invoke or affect the topic evolution. We assume that the semantic relatedness among the keywords can affect topic popularity during literature surveying and citing process, thus invoking evolution. However, the assumption is needed to be confirmed in an approach that fully considers the semantic interactions among topics. Traditional topic evolution analyses in scientometric domains cannot provide such support because of using limited semantic meanings. To address this problem, we apply the Google Word2Vec, a deep learning language model, to enhance the keywords with more complete semantic information. We further develop the semantic space as an urban geographic space. We analyze the topic evolution geographically using the measures of spatial autocorrelation, as if keywords are the changing lands in an evolving city. The keyword citations (keyword citation counts one when the paper containing this keyword obtains a citation) are used as an indicator of keyword popularity. Using the bibliographical datasets of the geographical natural hazard field, experimental results demonstrate that in some local areas, the popularity of keywords is affecting that of the surrounding keywords. However, there are no significant impacts on the evolution of all keywords. The spatial autocorrelation analysis identifies the interaction patterns (including High-High leading, High-Low suppressing) among the keywords in local areas. This approach can be regarded as an analyzing framework borrowed from geospatial modeling. Moreover, the prediction results in local areas are demonstrated to be more accurate if considering the spatial autocorrelations.  相似文献   

基于核心-边缘理论的中国汽车产业发展研究     

吕康娟  付曼杰 《软科学》2009,23(2)

将核心-边缘理论具体运用于汽车产业,通过系统动力分析和美、日汽车产业核心的实例,具体阐述了核心-边缘模式自发形成和自我维持的过程。同时使用位序-规模回归和聚类分析,定量测算我国汽车产业的聚集度,界定出上海、吉林为我国汽车产业的两大核心,而"上海嘉定国际汽车城"为我国唯一已经初步形成核心-边缘模式雏形的汽车产业核心,将其与世界其他国家汽车产业核心比较,对其发展提出建议。  相似文献   

空间密度聚类在数字图书馆图像检索中的应用     

王华秋  王重阳  聂珍 《现代情报》2016,36(2):129-134

图像聚类为数字图书馆图像管理提供了新的技术支持,能够在大量图像数据中发掘使用户感兴趣的信息。传统应用于图像聚类的特征提取算法往往忽略图像颜色的空间分布信息,且适应性较差。通过等面积矩形环对图像进行划分并计算各空间区域的相关性,并根据空间区域相关性计算各区域的重要性,将空间信息与颜色信息进行融合。同时对快速搜索密度峰值聚类算法的截断距离进行了合理改进,在保证聚类精度的同时提高收敛速度。最后将该密度聚类算法应用于数字图书馆图像检索之中。通过实验验证,本文提出的方法是可行的、有效的。  相似文献   

A relevance feedback mechanism for cluster-based retrieval     

Niall Rooney  David Patterson  Mykola Galushka  Vladimir Dobrynin 《Information processing & management》2006

Contextual document clustering is a novel approach which uses information theoretic measures to cluster semantically related documents bound together by an implicit set of concepts or themes of narrow specificity. It facilitates cluster-based retrieval by assessing the similarity between a query and the cluster themes’ probability distribution. In this paper, we assess a relevance feedback mechanism, based on query refinement, that modifies the query’s probability distribution using a small number of documents that have been judged relevant to the query. We demonstrate that by providing only one relevance judgment, a performance improvement of 33% was obtained.  相似文献   

Topic discovery based on text mining techniques     

Aurora Pons-Porrata  Rafael Berlanga-Llavori  José Ruiz-Shulcloper 《Information processing & management》2007

In this paper, we present a topic discovery system aimed to reveal the implicit knowledge present in news streams. This knowledge is expressed as a hierarchy of topic/subtopics, where each topic contains the set of documents that are related to it and a summary extracted from these documents. Summaries so built are useful to browse and select topics of interest from the generated hierarchies. Our proposal consists of a new incremental hierarchical clustering algorithm, which combines both partitional and agglomerative approaches, taking the main benefits from them. Finally, a new summarization method based on Testor Theory has been proposed to build the topic summaries. Experimental results in the TDT2 collection demonstrate its usefulness and effectiveness not only as a topic detection system, but also as a classification and summarization tool.  相似文献   

金边瑞香茎尖外植体快繁技术的研究     

李先良 《荆门职业技术学院学报》2007,22(9):12-15

以金边瑞香茎尖为外植体,探讨了不同培养基对丛生芽的诱导增殖、芽苗生根的影响。结果表明:1)金边瑞香丛生芽的诱导增殖可用培养基B5大量无机成分 MS微量无机成分 B5维生素 BA2.0 mg.L-1;2)丛生芽形成一定高度的芽苗后,接入培养基1/2B5 NAA50 mg.L-1中培养10 d,然后接入1/2B5培养基中可获得最佳生根效果.  相似文献   

Fitting Unstructured Finite Mixture Models in Longitudinal Design: A Recommendation for Model Selection and Estimation of the Number of Classes     

Naoya Todo 《Structural equation modeling》2016,23(5):695-712

In longitudinal design, investigating interindividual differences of intraindividual changes enables researchers to better understand the potential variety of development and growth. Although latent growth curve mixture models have been widely used, unstructured finite mixture models (uFMMs) are also useful as a preliminary tool and are expected to be more robust in identifying classes under the influence of possible model misspecifications, which are very common in actual practice. In this study, large-scale simulations were performed in which various normal uFMMs and nonnormal uFMMs were fit to evaluate their utility and the performance of each model selection procedure for estimating the number of classes in longitudinal designs. Results show that normal uFMMs assuming invariance of variance–covariance structures among classes perform better on average. Among model selection procedures, the Calinski–Harabasz statistic, which has a nonparametric nature, performed better on average than information criteria, including the Bayesian information criterion.  相似文献   

基于语义描述的煤矿安全监测数据聚类分析算法     

孟凡荣  周勇  夏士雄 《东南大学学报》2008,24(3)

为了挖掘基于语义描述的煤矿安全监测数据中蕴含的生产安全信息,指导煤矿安全生产和决策,研究了基于语义描述的煤矿安全监测数据聚类分析算法.首先,阐述了煤矿安全监测数据的语义和数值混合描述方法;接着,分别给出了语义和数值数据的相似性度量方法,以及基于权重的煤矿安全监测数据的混合相似性度量方法;然后,以混合相似性度量方法为距离度量准则,并借鉴网格的思想,给出了基于网格的改进CURE聚类算法.通过煤矿安全监测数据集的仿真实验,验证了所提算法的有效性.  相似文献   

我国科技期刊专业集群化网络出版平台研究   总被引：2，自引：1，他引：1  

迟秀丽  侯春梅  贺郝钰 《编辑学报》2015,27(2):182-185

介绍国内外科技期刊专业集群化网络出版平台的现状.通过对典型案例的分析,归纳总结我国科技期刊专业集群化网络出版平台的优势及其存在的主要问题,探讨专业集群化网络出版平台未来的发展,为我国科技期刊专业集群化网络出版平台今后发展提供参考.  相似文献