网络动态海报《随传随到》的多模态话语分析

作为数字传播时代的新兴产物,动态海报具有画面表现力强、传递信息量大、受众参与度高等特征,已广泛应用于网络广告领域。研究基于多模态话语分析综合理论框架,辅之以视觉语法理论,解析网络动态海报《随传随到》运用多模态符号资源实现的积极广告传播效果。研究发现：文化层面,意识形态是理解动态海报和实现广告传播效果的必要前提;语境层面,语境因素是动态海报产生特征和积极广告传播效果的动因;内容层面,广告传播效果取决于多模态资源在意义构建中的运用;表达层面,GIF格式文件为动态海报达到积极广告传播效果提供了技术支持。研究结合广告学知识探索了多模态话语分析在网络动态海报中的应用,旨在为动态海报的广告传播效果提供语言学解释。     

A simple two-step procedure using the Fellegi–Sunter model for frequency-based record linkage

The widely used Fellegi–Sunter model for probabilistic record linkage does not leverage information contained in field values and consequently leads to identical classification of match status regardless of whether records agree on rare or common values. Since agreement on rare values is less likely to occur by chance than agreement on common values, records agreeing on rare values are more likely to be matches. Existing frequency-based methods typically rely on knowledge of error probabilities associated with field values and frequencies of agreed field values among matches, often derived using prior studies or training data. When such information is unavailable, applications of these methods are challenging. In this paper, we propose a simple two-step procedure for frequency-based matching using the Fellegi–Sunter framework to overcome these challenges. Matching weights are adjusted based on frequency distributions of the agreed field values among matches and non-matches, estimated by the Fellegi–Sunter model without relying on prior studies or training data. Through a real-world application and simulation, our method is found to produce comparable or better performance than the unadjusted method. Furthermore, frequency-based matching provides greater improvement in matching accuracy when using poorly discriminating fields with diminished benefit as the discriminating power of matching fields increases.     

Intersubjectivity: Towards a Dialogical Analysis

Intersubjectivity refers to the variety of possible relations between perspectives. It is indispensable for understanding human social behaviour. While theoretical work on intersubjectivity is relatively sophisticated, methodological approaches to studying intersubjectivity lag behind. Most methodologies assume that individuals are the unit of analysis. In order to research intersubjectivity, however, methodologies are needed that take relationships as the unit of analysis. The first aim of this article is to review existing methodologies for studying intersubjectivity. Four methodological approaches are reviewed: comparative self-report, observing behaviour, analysing talk and ethnographic engagement. The second aim of the article is to introduce and contribute to the development of a dialogical method of analysis. The dialogical approach enables the study of intersubjectivity at different levels, as both implicit and explicit, and both within and between individuals and groups. The article concludes with suggestions for using the proposed method for researching intersubjectivity both within individuals and between individuals and groups.     

The ratification of ILO Conventions and the provision of unemployment benefits: An empirical analysis

This article tests the relationship between the ratification of International Labour Organization (ILO) Conventions and the provision of unemployment benefits. Statistical tests focus on two related issues: why countries ratify ILO Conventions on unemployment benefits, and whether ratification influences government spending on unemployment benefits. The main findings are that democracy, region, income, and globalization are the main factors influencing why countries ratify ILO Conventions on unemployment benefits. In turn, the ratification of ILO Conventions is systematically associated with higher spending if countries have ratified more than two Conventions.     

Semantic Analysis of the Theoretical Foundations of Biology

生物学理论作为科学哲学研究中的一个另类一直受到关注。它与传统科学模式间的差异是造成这种现象的原因之一。解读这种差异的根源,需要对生物学的理论基础以及理论结构给予充分的关注。生物学特有理论结构所表现出的多元语境与语义结构的复杂性,决定了对生物学理论基础的研究应当重视语义分析的方法,尤其是对理论本身进行语义分解并研究其中的语义关联问题,从而解读生物学模式作为一种不同于理化科学的特殊科学解释观的合理性。     

Semiparametric Bayesian classification with longitudinal markers

Summary.  We analyse data from a study involving 173 pregnant women. The data are observed values of the β human chorionic gonadotropin hormone measured during the first 80 days of gestational age, including from one up to six longitudinal responses for each woman. The main objective in this study is to predict normal versus abnormal pregnancy outcomes from data that are available at the early stages of pregnancy. We achieve the desired classification with a semiparametric hierarchical model. Specifically, we consider a Dirichlet process mixture prior for the distribution of the random effects in each group. The unknown random-effects distributions are allowed to vary across groups but are made dependent by using a design vector to select different features of a single underlying random probability measure. The resulting model is an extension of the dependent Dirichlet process model, with an additional probability model for group classification. The model is shown to perform better than an alternative model which is based on independent Dirichlet processes for the groups. Relevant posterior distributions are summarized by using Markov chain Monte Carlo methods.     

Bayesian analysis of human movement curves

Summary.  We consider the Bayesian analysis of human movement data, where the subjects perform various reaching tasks. A set of markers is placed on each subject and a system of cameras records the three-dimensional Cartesian co-ordinates of the markers during the reaching movement. It is of interest to describe the mean and variability of the curves that are traced by the markers during one reaching movement, and to identify any differences due to covariates. We propose a methodology based on a hierarchical Bayesian model for the curves. An important part of the method is to obtain identifiable features of the movement so that different curves can be compared after temporal warping. We consider four landmarks and a set of equally spaced pseudolandmarks are located in between. We demonstrate that the algorithm works well in locating the landmarks, and shape analysis techniques are used to describe the posterior distribution of the mean curve. A feature of this type of data is that some parts of the movement data may be missing—the Bayesian methodology is easily adapted to cope with this situation.     

Comparison of different estimation techniques for portfolio selection

The main problem in applying the mean-variance portfolio selection consists of the fact that the first two moments of the asset returns are unknown. In practice the optimal portfolio weights have to be estimated. This is usually done by replacing the moments by the classical unbiased sample estimators. We provide a comparison of the exact and the asymptotic distributions of the estimated portfolio weights as well as a sensitivity analysis to shifts in the moments of the asset returns. Furthermore we consider several types of shrinkage estimators for the moments. The corresponding estimators of the portfolio weights are compared with each other and with the portfolio weights based on the sample estimators of the moments. We show how the uncertainty about the portfolio weights can be introduced into the performance measurement of trading strategies. The methodology explains the bad out-of-sample performance of the classical Markowitz procedures.     

基于RS分析的中国债券市场分形特征研究

文章详细讨论了RS分析方法、概率空间分形维的测度,通过对上证国债指数和上证企债指数的RS分析,得到了两序列赫斯特指数和非周期循环长度,进一步得出中国债券市场为分形市场的结论.