A review of topic modeling methods

Topic modeling is a popular analytical tool for evaluating data. Numerous methods of topic modeling have been developed which consider many kinds of relationships and restrictions within datasets; however, these methods are not frequently employed. Instead many researchers gravitate to Latent Dirichlet Analysis, which although flexible and adaptive, is not always suited for modeling more complex data relationships. We present different topic modeling approaches capable of dealing with correlation between topics, the changes of topics over time, as well as the ability to handle short texts such as encountered in social media or sparse text data. We also briefly review the algorithms which are used to optimize and infer parameters in topic modeling, which is essential to producing meaningful results regardless of method. We believe this review will encourage more diversity when performing topic modeling and help determine what topic modeling method best suits the user needs.     

Changes in transitions from private renting to homeownership in the context of rapidly rising house prices

A period associated with the emergence of the current housing crisis in Britain provides a testbed in which to investigate household tenure choice in the context of rapidly rising house prices. We compile a bespoke data-set combining data from the British Household Panel Survey and sources of local and national housing and mortgage market information covering the period 1994–2008. During this period, we observe three key changes in behaviour associated with the emergence of the housing crisis: (i) increasing acceptance of long-term renting; (ii) the emergence of local house prices as a factor inhibiting entry to homeownership at district level; and (iii) the cessation of moving to a lower cost district as a strategy to enter homeownership. We interpret these findings as some private tenants reducing their aspiration for homeownership, and those seeking entry to homeownership shifting strategy from moving to cheaper districts in favour of staying put and saving.     

The value of big data for credit scoring: Enhancing financial inclusion using mobile phone data and social network analytics

Credit scoring is without a doubt one of the oldest applications of analytics. In recent years, a multitude of sophisticated classification techniques have been developed to improve the statistical performance of credit scoring models. Instead of focusing on the techniques themselves, this paper leverages alternative data sources to enhance both statistical and economic model performance. The study demonstrates how including call networks, in the context of positive credit information, as a new Big Data source has added value in terms of profit by applying a profit measure and profit-based feature selection. A unique combination of datasets, including call-detail records, credit and debit account information of customers is used to create scorecards for credit card applicants. Call-detail records are used to build call networks and advanced social network analytics techniques are applied to propagate influence from prior defaulters throughout the network to produce influence scores. The results show that combining call-detail records with traditional data in credit scoring models significantly increases their performance when measured in AUC. In terms of profit, the best model is the one built with only calling behavior features. In addition, the calling behavior features are the most predictive in other models, both in terms of statistical and economic performance. The results have an impact in terms of ethical use of call-detail records, regulatory implications, financial inclusion, as well as data sharing and privacy.     

融合社交网络和图像内容的兴趣点推荐

基于位置的社交网络（LBSN）蓬勃发展，带来了大量的兴趣点（POI）数据，加速了兴趣点推荐的研究。针对用户-兴趣点矩阵极端稀疏造成的推荐精度低和兴趣点特征缺失问题，通过融合兴趣点的标签、地理、社交、评分以及图像等信息，提出了一种融合社交网络和图像内容的兴趣点推荐方法（SVPOI）。首先分析兴趣点数据集，针对地理信息，利用幂律概率分布构造距离因子；针对标签信息，利用检索词频率构造标签因子；融合已有的历史评分数据，构造新的用户-兴趣点评分矩阵。其次利用VGG16深度卷积神经网络模型（DCNN）识别兴趣点图像内容，构造兴趣点图像内容矩阵。然后根据兴趣点数据的社交网络信息，构造用户社交矩阵。最后，利用概率矩阵分解（PMF）模型，融合用户-兴趣点评分矩阵、图像内容矩阵、用户社交矩阵，构成SVPOI兴趣点推荐模型，生成兴趣点推荐列表。大量的真实数据集上的实验结果表明，与PMF、SoRec、TrustMF、TrustSVD推荐算法相比，SVPOI推荐的准确度均有较大提升，其平均绝对误差（MAE）和均方根误差（RMSE）两项指标比最优的TrustMF算法分别降低了5.5%和7.82%，表明SVPOI具有更好的推荐效果。     

Analysis of critical factors for social games based on extended technology acceptance model: a DEMATEL approach

In recent years, social games such as ‘Farmville’ and ‘Pokémon Go’ have become a major game type in the gaming industry. This study examines the importance of different factors in social games using the Technology Acceptance Model (TAM) and DEMATEL. The result shows ‘social norm’ as the most important factor overall. It is also found that ‘pleasure’ and ‘sociability’ are the most important aspects in ‘perceived enjoyment’. Regarding key aspects in each factor, ‘flow experience’ is crucial in ‘perceived attractiveness’, ‘game fairness’ largely influential in ‘social norm’, and ‘reputation of platform and service provider’ a decisive aspect in ‘platform service and corporate image’. These findings and analyses are apt references for social game providers to improve their services.     

A strategy to optimize the multi-energy system in microgrid based on neurodynamic algorithm

In this paper, we design multi-energy management strategy for power-supply participants, heat-supply participants and consumers in a microgrid. The objectives of the management strategy are to maximize the social welfare and to balance the energy supply and demands. With the transmission loss, the proposed social welfare model, subject to practical operation constraints, is formulated as a nonconvex optimization problem. Based on a sufficient condition, a equivalent problem transformed from the primary optimization problem is presented as a convex problem. A neurodynamic algorithm based Karush–Kuhn–Tucker(KKT) conditions and projection with fewer neurons is developed to regulate the resource output of each participant. The convergence of the applied algorithm is proved by Lyapunov function. Finally, numerical simulations are used to prove the effectiveness of the designed management strategy.     

What are the impacts of living in social housing? New evidence from Australia

Abstract

In this paper, we apply statistical matching methods to a national longitudinal dataset of Australians facing housing insecurity to estimate the impacts of social housing on employment, education, health, incarceration and homelessness. We find social housing in Australia provides an important `safety net’ protecting people from homelessness. However, at least in the short run, individuals in social housing have similar outcomes in terms of employment, education, physical and mental health, and incarceration to other comparable individuals not in social housing. These are the first estimates of causal impacts of social housing, simultaneously estimating impacts on a range of shelter and non-shelter outcomes highlighted as important by the broader social housing literature. They also provide an interesting contrast with the existing US estimates. These results are potentially due to strict targeting of individuals into social housing and that they represent the average effect across individuals who may experience substantially different impacts.     

Comparative analysis of different design of rotary dehumidifier

A one‐dimensional mathematical model has been developed to do the comparative analysis of four design of the desiccant wheel. The mathematical model has been validated with experimental results and shows good agreements with experimental results. In this study, a two‐sector desiccant wheel is modified into a three‐sector wheel by introducing a purge section in the desiccant wheel. Similarly, a four‐sector desiccant wheel is reformed into a six‐sector wheel by installing two purge section in the desiccant wheel and comparative study of these designs have been carried for given ranges of operating conditions. The effect of purge conditions has been also investigated and found that in all operating conditions six‐sector design is a better choice for optimum MRC and ?T.     

Detachment in Planning Practice

Despite increasing privatization of planning, little is known about the practices, feelings, and values of planners in the private sector. Likewise, although scholars acknowledge the potential regressive outcomes of planning, the involvement of planners in regressive practices remains understudied. This paper focuses on the practices of private sector planning professionals involved in the making of suburban gated communities in Brazil. The analysis reveals that these planners understand their practices through a narrow lens as they approach planning through political, professional, and valuative detachment.