企业网上社区用户忠诚度影响因素的实证分析

提高用户对网上社区的忠诚度将有助于电子商务网站吸引和保持客户。忠诚的用户不仅自身积极参与网站的交易,而且其言论将对其他用户产生正面且重要的影响。模型假设用户信任及虚拟社区感对忠诚度具有显著作用。虚拟社区感包括三个维度：成员感、影响力、需求满足。对收集的195份有效样本数据采用PLS Graph进行分析,结果发现用户信任显著影响虚拟社区感的三个维度与忠诚度,表明用户信任对于网上社区运作所发挥的基础性作用。此外,在虚拟社区感的三个维度中,仅有需求满足显著影响用户忠诚度。     

电子商务网站设计研究

电子商务是未来商务交易的主要运营方式,电子商务网站是电子商务的主要承担者和表现者,电子商务网站设计是企业开展电子商务的关键环节。文章分别从系统和用户的角度分析了电子商务网站设计的原则,并从总体上对电子商务网站设计的核心内容：商务模式设计、功能设计、结构设计、管理设计等进行了探讨。参考文献6。     

社会媒体用户标签的分析与推荐

微博是Web2.0时代重要的网络服务工具,作为以用户为中心的信息发布、传播和分享平台,它包含了非常丰富的用户信息。在微博中,可以使用标签表示用户的兴趣和属性。而一个用户的兴趣和属性,通常包含在这个用户的文本信息和网络信息中。针对微博用户的标签进行分析,提出网络正则化的标签分发模型（NTDM）来为用户推荐标签。NTDM模型对用户个人简介中的词语和标签之间的关系进行建模,同时利用其社交网络结构作为模型的正则化因子。在真实数据集上的实验表明,NTDM在效果以及效率上都优于其他方法。     

Online Contact,Face-to-Face Contact,and Multilingualism: Young Swedish-Speaking Finns Develop Trilingual Identities

Based on the tenets of the social context model of second language acquisition, the present article examined the combined effect of online and face-to-face contact in developing multilingual skills and identities among young Swedish-speaking Finns (N = 304). The hypotheses were tested for Finnish as a second language and English as a third language using parallel models. The results were largely identical for both languages. Specifically, online contact enhanced language confidence which, in turn, contributed to language identity. However, online contact had a more substantial effect on confidence as well as identity among those who had little face-to-face contact with speakers of the given language. Findings and their implications are discussed.     

基于点击流的电商用户会话建模

[目的/意义] 鉴于已有基于点击流的用户模型大多简单地采用页面类型序列代替行为序列,提出一种根据点击流访问页面序列到用户行为的映射方案,解决用户行为建模的问题。[方法/过程] 本文在分析网页URL参数、页面内容等特征的基础上,以81 759个电商用户会话为测试样本,提出并实现从页面到用户行为的映射方法,给出一种依据原始日志建立用户行为序列来描述会话的方案。[结果/结论] 分析反映出在会话层面上已有研究不易得到的行为特征,得到6类具备不同行为模式的会话:功能探索会话、卖家管理会话、营销推动会话、资料管理会话、商品浏览会话、检索依赖会话。基于点击流对用户会话建模,可以得出用户会话中行为序列特征,对实现准确营销与推荐具有重要价值。     

基于TAM/TTF整合的电子商务用户接受模型

在信息技术接受研究中,TRA、TPB、TAM、TTF等用户接受模型得到广泛证实和应用。在模型分析和比较的基础上,对电子商务环境下任务、技术、用户三者所表现出的特征进行总结。最后,基于TAM、TPB和TTF等信息技术接受模型,根据CNNIC和开放式问卷调查的数据统计结果,构建出电子商务用户接受理论模型。     

Formation of a talking space and gender discourses in digital diaspora space: Case of a female Korean im/migrants online community in the USA

This article explores an online community of female Korean im/migrants in the USA in order to investigate the formation of a digital diaspora of women on the web. Employing multiple research methods including in-depth interviews, textual analysis, and participatory observation, this article examines the largest online community of female Korean im/migrants in the USA (www.MissyUSA.com), focusing on how their unique talking space was created on this site and the ways in which the relevant gender discourses are presented and constructed in relation to their diasporic conditions. The findings show that these women's shared identity (i.e. being Korean, married, female, and living in the USA) is an important element in the formation and development of this online community, especially in the creation of a candid talking space – sokpuri – where they vent their innermost feelings about their lives in the USA. The Missy and ajuma are the two salient identity discourses and selective use and flexible appropriation of the terms are found. The ajuma image (less individualistic, more active in sharing information and helping others) is adopted when these women identify their online community as a place where the empowering ajuma spirit is alive; meanwhile, they still adopt the Missy image of a young, independent, and modern woman for their individual identities, despite its consumerist origin. Although the issues of housewifization and having an enhanced gender relationship are quite often discussed, this online community has a limitation in that it does not produce a consistent and systematic challenging voice.     

一个新的基于协作过滤的用户浏览预测模型

本文提出了一个新的基于协作过滤的用户浏览协作预测模型———UNCPM ,它有效地解决了目前协作过滤预测方法的准确性和覆盖率低等问题。UNCPM从Web日志中获取用户浏览信息 ,系统分为两个部分 :离线构件和在线构件。离线构件用于用户浏览历史记录的K means聚类 ,并在聚类时充分考虑URL的相似分析来避免协作过滤的同义性和分散性等不足 ;在线构件用于活动用户预测。该模型可以应用在大型电子商务网站的用户浏览预测上。     

Forecasting user visits for online display advertising

Online display advertising is a multi-billion dollar industry where advertisers promote their products to users by having publishers display their advertisements on popular Web pages. An important problem in online advertising is how to forecast the number of user visits for a Web page during a particular period of time. Prior research addressed the problem by using traditional time-series forecasting techniques on historical data of user visits; (e.g., via a single regression model built for forecasting based on historical data for all Web pages) and did not fully explore the fact that different types of Web pages and different time stamps have different patterns of user visits. In this paper, we propose a series of probabilistic latent class models to automatically learn the underlying user visit patterns among multiple Web pages and multiple time stamps. The last (and the most effective) proposed model identifies latent groups/classes of (i) Web pages and (ii) time stamps with similar user visit patterns, and learns a specialized forecast model for each latent Web page and time stamp class. Compared with a single regression model as well as several other baselines, the proposed latent class model approach has the capability of differentiating the importance of different types of information across different classes of Web pages and time stamps, and therefore has much better modeling flexibility. An extensive set of experiments along with detailed analysis carried out on real-world data from Yahoo! demonstrates the advantage of the proposed latent class models in forecasting online user visits in online display advertising.     

Discourses of Disability,Narratives of Community: Reclaiming an Autistic Identity Online

As increasing rates of autism diagnosis generate media interest, the autism community is bombarded with various disability discourses. Using netnographic methods, I explored how members of one online community, Aspies Central (AC), engaged these discourses to communicatively (re)claim a positive autistic identity. By assessing 561 posts on AC's forums, interviewing 10 individuals who frequent online communities, and interacting extensively with two informants, I located reclaiming discourses that allowed community members to shift their understanding of autism from a biomedical to a cultural perspective. Through these discourses, community members reclaimed (a) normalcy, (b) symptoms, and (c) agency. In this paper, I discuss implications for the narrative construction of disability identities and the activation of self-advocacy movements.     

基于社区Web日志挖掘的用户行为实证研究

用户访问行为信息记录在Web日志中,通过对海量Web日志进行清洗、抽取和加载来构建用户行为数据仓库,并结合文章所提出的用户访问路径概率矩阵模型进行数据挖掘,可以实现智能化的用户行为监控,可以为用户提供及时优质的信息服务。     

Predicting mobile government service continuance: A two-stage structural equation modeling-artificial neural network approach

Retaining users of mobile government services (MGS) is critical to the success of mobile government. Drawing on Bagozzi's self-regulation framework, the current research investigates the predictors of MGS continuance by considering both perceived quality and perceived value. Unlike most e-government research that has utilized linear models, this study employed a two-stage structural equation modeling–artificial neural network approach that can identify non-linear and non-compensatory interactions. The current research first applied a structural equation model to examine the significant factors influencing MGS continuance, and then utilized a neural network model recheck the structural equation modeling findings and rank the importance of these factors. Data were obtained from 335 “one-stop-shop service platform” app users in China through an online survey platform. The research findings reveal that user satisfaction is the utmost influential determinant of their continuous-use intention regarding MGS, followed by user trust; moreover, perceived quality and perceived value strongly influence satisfaction and trust. However, perceived risk does not affect intention to continue use. We also discuss theoretical and practical implications for government agencies and service providers, for improving user continuance rates for MGS.     

用户认知导向的网络信息搜索模型研究述评

网络信息搜索行为与用户的日常生活息息相关,用户认知导向的网络信息搜索是认知观和社会认知理论在网络信息搜索中的应用,是与传统信息检索和用户导向信息检索不同的检索范式。在介绍认知交互模型、信息问题解决模型和使用搜索引擎的网络信息搜索行为模型等用户认知导向的信息搜索模型的基础上,进一步从用户因素、信息环境和社会情境方面分析网络信息搜索过程中的影响因素。     

The Suitability of Web Analytics Key Performance Indicators in the Academic Library Environment

As the demand for library assessment grows, academic libraries are becoming more interested in Web analytics. Data are automatically gathered and provide information about a wide variety of online interactions. Libraries have long used simple counts such as visits and page views, but have more recently begun to choose strategic benchmarks, also known as key performance indicators (KPIs). Many common KPIs were created for commercial websites and are challenging to adapt for libraries. However, the underlying concepts are sufficiently valuable that libraries should explore their use. By evaluating the validity of web metrics, libraries can further the development of standards and benchmarks to support future investigations. This article discusses how commercial web metrics might be adapted for use in academic libraries. First, the limitations of web analytics are presented. Major key performance indicators used in the commercial sector are reviewed in the academic library context. Finally, the article discusses how the various indicators might support specific library website goals and decisions and uses local data to illustrate one example case. As libraries choose web analytic methods, they should deliberately evaluate their validity. Over time, this will slowly build the profession's ability to use web analytics more effectively for library assessment.     

B2C电子商务中用户认知信息检索模型的分析——以当当网和卓越网为例

结合Kuhlthau 6阶模型以及信息检索在认知上发生的重大变化和转折,以当当网和卓越网为例,分析用户认知信息检索的主要指标,在此基础上提出B2C电子商务的用户认知信息检索模型,并对其内在结构和工作原理进一步作认知分析,为我国B2C电子商务企业构造信息检索模型提供基本思路。     

Unfulfilled: A Story of Users and Library Request Services

The current technology models for library request services present significant challenges for the user’s experience from discovery to delivery. Applying user-centered design and e-commerce modalities may allow libraries to create more engaging and useful request services for all users. The authors suggest six design principles to improve user’s experience with library request systems and offer practical applications of these principles based upon two case studies at The New School Libraries and New York University Libraries. Both cases utilize APIs currently available, suggesting that libraries may leverage current models to create a better experience for their users.     

当代省级公共图书馆网络在线服务状况

21世纪省级公共图书馆如何充分利用网络环境为本地区的经济建设、文化事业服务，如何有效满足广大用户各种个性化的信息需求，如何加强构建信息资源保障体系，特别是如何提供包括传统图书期刊的网上流通、现代电子资源的网上查询、虚拟参考咨询的网上服务、文化信息资源的共享建设等在内的网络在线服务应用实践，是摆在我们面前的一项重要任务，本文对此进行了解读。     

基于Web挖掘技术的用户兴趣本体学习研究

目前针对基于关键词的用户模型不能从语义上表达用户需求真正内涵,基于领域本体的用户模型多数忽略研究概念间非分类关系和语义应用环境较分散等缺陷。本文提出一种循环式的基于Web挖掘技术的用户兴趣本体学习模型,即综合应用统计分析、关联规则和聚类分析等技术进行电子商务领域用户兴趣概念及概念间分类与非分类关系学习,面对用户兴趣的迅速变化,还提出一种传递激活方法来实时更新本体或重新进行本体学习,以不断提高该本体的质量。经验证,基于该本体的用户模型在文本过滤等应用中能较上述两种用户模型满足用户个性化服务需求。     

Can you see me now?: Engaging distance learners through virtual reference consultations

Research consultations continue to be a valuable service offered by academic libraries for students who are able to visit the library, however, most students enrolled in online degree programs or considering enrollment have limited access to campus services. To address this, the authors designed and tested a virtual reference consultation service in their library for distance learners and graduate students. This article outlines a practical approach for designing and initiating a virtual research consultation service pilot, providing equitable access to library services and a positive user experience for distance learners.