社会网络应用中数据迁移的隐私风险模式研究

由于在社会网络应用程序站点上自愿添加个人身份信息的人数不断增加,站点服务商可以从中获益,但是同时数据误用的风险会威胁个人用户的隐私信息以及服务商的商业模式。本文根据最近的调查,分析了开发隐私保护社会网络应用的主要需求,在此基础上提出了隐私风险模式,以增强数据或社会网络迁移过程中的信息隐私保护。通过确定与个人身份信息迁移过程中重要的问题设计出了该隐私风险模式。     

在线社交网络中好友亲密度判定方法研究

与现实生活中的朋友关系不同,多数的在线社交网络系统为每个人只设定一个简单的二元好友联系,即要么是朋友,要么不是。这种好友关系的定义为个人隐私信息的保护带来了许多问题。分析了一种基于当前社交网络平台的互动信息自动判定好友亲密度方法,并结合该方法提出了一种半自动的隐私控制框架。     

A social status perspective of network utility over electronic channels in academic communities

Early research on the social implications of e-mail has promoted the role of electronic communication channels in fostering social equality and reducing gaps between the social classes. Follow-up studies, however, suggest that people continue to rely on social cues in electronic communication as a way of dealing with uncertainties and reducing feelings of discomfort associated with unfamiliar contexts. Based on a review of the Social Cognitive Theory, social status and electronic communication literatures, along with the results of a previous qualitative study, we propose a formal model that indicates how self-perceptions of social status are related to the use of e-mail and the acquisition of social resources over electronic channels. The model is tested using data collected from 206 faculty members in a major U.S. university. The empirical results support the proposed model implying that self-perceptions of social status influence social assertiveness, which in turn reinforces the use of e-mail to seek help and acquire social resources from others. The use of e-mail for the acquisition of social resources is associated with a socially diverse network whose contacts are perceived to acquire valuable information and to extend instrumental support for career development. Implications are drawn for both theory and practice.     

Visualization of the Nordic academic web: Link analysis using social network tools

The aim of this paper is to study the link relationships in the Nordic academic web space – comprised of 23 Finnish, 11 Danish and 28 Swedish academic web domains with the European one. Through social networks analysis we intend to detect sub-networks within the Nordic network, the position and role of the different university web domains and to understand the structural topology of this web space. Co-link analysis, with asymmetrical matrices and cosine measure, is used to identify thematic clusters. Results show that the Nordic network is a cohesive network, set up by three well-defined sub-networks and it rests on the Finnish and Swedish sub-networks. We conclude that the Danish network has less visibility than other Nordic countries. The Swedish one is the principal Nordic sub-network and the Finland network is a slightly isolated from Europe, with the exception of the University of Helsinki.     

Social network data to alleviate cold-start in recommender system: A systematic review

Recommender Systems are currently highly relevant for helping users deal with the information overload they suffer from the large volume of data on the web, and automatically suggest the most appropriate items that meet users needs. However, in cases in which a user is new to Recommender System, the system cannot recommend items that are relevant to her/him because of lack of previous information about the user and/or the user-item rating history that helps to determine the users preferences. This problem is known as cold-start, which remains open because it does not have a final solution. Social networks have been employed as a good source of information to determine users preferences to mitigate the cold-start problem. This paper presents the results of a Systematic Literature Review on Collaborative Filtering-based Recommender System that uses social network data to mitigate the cold-start problem. This Systematic Literature Review compiled the papers published between 2011–2017, to select the most recent studies in the area. Each selected paper was evaluated and classified according to the depth which social networks used to mitigate the cold-start problem. The final results show that there are several publications that use the information of the social networks within the Recommender System; however, few research papers currently use this data to mitigate the cold-start problem.     

A relevance model for a data warehouse contextualized with documents

This paper presents a relevance model to rank the facts of a data warehouse that are described in a set of documents retrieved with an information retrieval (IR) query. The model is based in language modeling and relevance modeling techniques. We estimate the relevance of the facts by the probability of finding their dimensions values and the query keywords in the documents that are relevant to the query. The model is the core of the so-called contextualized warehouse, which is a new kind of decision support system that combines structured data sources and document collections. The paper evaluates the relevance model with the Wall Street Journal (WSJ) TREC test subcollection and a self-constructed fact database.     

Connection and stratification in research collaboration: An analysis of the COLLNET network

Co-authorship among scientists represents a prototype of a social network. By mapping the graph containing all relevant publications of members in an international collaboration network: COLLNET, we infer the structural mechanisms that govern the topology of this social system. The structure of the network affects the information available to individuals, and their opportunities to collaborate. The structure of the network also affects the overall flow of information, and the nature of the scientific community. We present a number of measures of both the macro- (whole-network) and micro- (actor-centered) structure of collaboration, and apply these to COLLNET. We find that this scientific community displays many aspects of a “small-world,” and is somewhat vulnerable to disruption should major figures become inactive. We also find inequality in the roles played by individuals in the network. The inequalities, however, do not create a closed and isolated “core” or elite.     

Questioner or question: Predicting the response rate in social question and answering on Sina Weibo

With the noted popularity of social networking sites, people increasingly rely on these social networks to address their information needs. Although social question and answering is potentially an important venue seeking information online, it, unfortunately, suffers from a problem of low response rate, with the majority of questions receiving no response. To understand why the response rate of social question and answering is low and hopefully to increase it in the future, this research analyzes extrinsic factors that may influence the response probability of questions posted on Sina Weibo. We propose 17 influential factors from 2 different perspectives: the content of the question, and the characteristics of the questioner. We also train a prediction model to forecast a question's likelihood of being responded based on the proposed features We test our predictive model on more than 60,000 real-world questions posted on Weibo, which generate more than 600,000 responses. Findings show that a Weibo's question answerability is primarily contingent on the questioner versus the question. Our findings indicate that using appreciation emojis can increase a question's response probability, whereas the use of hashtags negatively influences the chances of receiving answers. Our contribution is in providing insights for the design and development of future social question and answering tools, as well as for enhancing social network users’ collaboration in supporting social information seeking activities.     

基于分类回归树和神经网络模型的零售商品促销数据分析与探讨

随着信息技术的不断发展,应用商业智能技术进行数据挖掘与分析对商家来说也越来越重要,分类回归树和神经网络算法是数据挖掘的经典算法,其广泛运用在数据分析、预测和评估等方面。文章分别运用分类回归树和神经网络算法对零售商品采取促销方案后收入变化的数据进行分析,并建立相应的模型对促销方案效果进行预测。     

网络环境下知识扩散的多智能体模型研究

知识扩散受到知识接收者学习能力、知识传播者声誉、人们之间的沟通状况等多方面因素影响。本文根据知识扩散的相关假说,将影响知识扩散的因素抽象为多智能体模型中的可控变量,利用多智能体模型模拟网络环境下的知识扩散过程,分析多智能体分布密度、单个智能体知识扩散范围、相同分布密度下多智能体的不同分布状况对知识扩散的范围、速度等的影响情况。     

PPT多媒体课件在教学应用中的常见问题与对策

文章通过分析教学中应用PPT多媒体课件常见的问题,提出相应的对策,避免出现多媒体教学应用中常见的文字堆叠,信息量过大等问题,使得PPT多媒体课件在教学中更能体现其形象直观的特点,更能发挥图片和动画的效果,使课件更好的辅助教师的授课,真正起到帮助教师提高教学的效果的作用。     

基于社会网络的家族企业竞争环境与战略选择

社会网络虽然可以在一定程度上解决中国当代家族企业随组织规模扩大而呈现的管理资源与管理能力不足等现实问题,但是随着企业竞争环境的发展,原有的资源配置、抗风险能力等功能将会进一步弱化,其面临的真正风险更多的来自于外部,即竞争环境的变化与产业价值链的调整与变革。这个时候企业的行为将更为理性化,家族企业在新的竞争环境下会进行新的战略选择。     

社会网络视角下中国创新管理学术团体研究

以10671篇创新管理研究论文为分析对象,运用社会网络分析方法,通过作者合著网络结构的量化分析,揭示了中国创新管理研究学术团体及其研究方向,进而对网络中重复出现的作者进行了数理统计和中心性分析,发现了作者机构流动效应,以期对我国创新管理研究的未来发展方向以及科研合作政策的制定提供有益启示。     

Leveraging social grouping for trust building in foreign electronic commerce firms: An exploratory study

Internet development has fueled e-commerce firms’ globalization efforts, but many have met with only limited success. This often stems from the foreign firms’ limited understanding of a focal country's local culture and idiosyncrasies. Foreign firms are usually viewed as out-group entities, which lowers consumers’ trust in them. The extent of such a phenomenon varies. In locations where people are more skeptical of out-groups, a critical question is whether it is possible to transform such foreign out-group firms into in-groups, specifically with the support of popular social networking media. Based on Social Identity Theory and Trust Transference Process, five strategies leveraging social grouping and social ties to build trust for foreign electronic commerce firms were proposed. A survey was conducted to examine their effectiveness. The results suggest that social-grouping strategies are useful for in-grouping foreign out-group entities to build trust, and the effectiveness of strategies is determined by the social similarity and psychological distance between the consumer and the endorser. This has important implications for scholars and practitioners, both local and abroad, to leverage social grouping to boost Internet sales.     

The basis for bibliomining: Frameworks for bringing together usage-based data mining and bibliometrics through data warehousing in digital library services

Over the past few years, data mining has moved from corporations to other organizations. This paper looks at the integration of data mining in digital library services. First, bibliomining, or the combination of bibliometrics and data mining techniques to understand library services, is defined and the concept explored. Second, the conceptual frameworks for bibliomining from the viewpoint of the library decision-maker and the library researcher are presented and compared. Finally, a research agenda to resolve many of the common bibliomining issues and to move the field forward in a mindful manner is developed. The result is not only a roadmap for understanding the integration of data mining in digital library services, but also a template for other cross-discipline data mining researchers to follow for systematic exploration in their own subject domains.     

Influence of social media on operational efficiency of national scenic spots in china based on three-stage DEA model

An increasing number of national scenic spots around the world use social media, such as micro-blogs and Twitter, to promote their popularity and improve their operational performance. National scenic spots may adopt different social media behaviors that lead to unbalanced operational performance. This study takes the perspective of social media adoption in national scenic spots by looking into the influence of social media adoption behaviors on operational performance based on the three-stage data envelopment analysis model. We found that most of the national scenic spots in China have low pure technical efficiency and that operational performance, including social media popularity and operational performance, is significantly determined by various social media adoption behaviors.     

The evolving relations between government agencies of innovation policymaking in emerging economies: A policy network approach and its application to the Chinese case

Literature on innovation policy reveals little of how relations between government agencies as policymakers evolve. Taking the policy network approach, this paper investigates three mechanisms underlining the evolution of inter-government agency relations in emerging economies – policy agenda, power concentration and heterogeneity dependence, and applies them to the analysis of the evolution of innovation policymaking in China. Operationally, the paper proposes a social network analysis (SNA)-based method to quantitatively study China’s innovation policy network, which consists of 463 innovation policy documents formulated by its central government ministries between 1980 and 2011. The findings show that the formal policy network for innovation has been not only sustained through the intervention of policy agendas but also self-organized because of policy network’s nature of power concentration and heterogeneity dependence. The presence of such mixed mechanisms in China’s innovation policy network’s evolution differs from the findings from industrialized countries where self-organization plays a central role. This work advances our theoretical understanding of the evolution of innovation policy network and has implications for innovation policymaking in emerging economies.     

A social recommender mechanism for improving knowledge sharing in online forums

Nowadays, online forums have become a useful tool for knowledge management in Web-based technology. This study proposes a social recommender system which generates discussion thread and expert recommendations based on semantic similarity, profession and reliability, social intimacy and popularity, and social network-based Markov Chain (SNMC) models for knowledge sharing in online forum communities. The advantage of the proposed mechanism is its relatively comprehensive consideration of the aspects of knowledge sharing. Accordingly, results of our experiments show that with the support of the proposed recommendation mechanism, requesters in forums can easily find similar discussion threads to avoid spamming the same discussion. In addition, if the requesters cannot find qualified discussion threads, this mechanism provides a relatively efficient and active way to find the appropriate experts.     

Rethinking the role of the state in technology development: DARPA and the case for embedded network governance

This paper explores the role of the state in re-architecting social networks and thereby new technology directions in the United States. It draws on a case study of DARPA's Microsystems Technology Office from 1992 to 2008. Leveraging one of the most radical directorships in DARPA's history, I argue that the perceived “death” of DARPA under Tony Tether was because past analyses, by focusing on the organization's culture and structure, overlooked a set of lasting, informal institutions among DARPA program managers. I find that despite significant changes in the recipients and outcomes of DARPA attentions, these same institutions for directing technology were in place both before and during Tether's directorship. Drawing on these results, I suggest that we must add to technology policy-making a new option—embedded network governance.