A targeted approach to viral marketing

Viral marketing can be an effective marketing technique in social networks. Initiating from a set of influential seed users, it can activate a “chain-reaction” driven by word-of-mouth. The effectiveness of viral marketing lies in the fact that it conveys an implied endorsement from social ties. Existing approaches to selecting influential seeds depend on measures of global centrality within the structure of the social network – they select users that are central in the entire network according to some centrality measure (e.g., Eigenvector centrality). In this paper a new targeted approach to viral marketing is proposed that exploits prior knowledge about the potential market and uses local centrality scores to identify seeds that have high chances of reaching and activating many users in the potential market. The performance gained by the proposed approach is investigated with an experimental evaluation that uses data from real social networks. The results show that targeted approach outperforms existing, global centrality based methods. It is also shown that the relative performance of the targeted approach improves in the case where the majority of users are indifferent (or negative) to the viral marketing campaign.     

Discovering influencers for marketing in the blogosphere

Discovering influential bloggers will not only allow us to understand better the social activities taking place in the blogosphere, but will also provide unique opportunities for sales and advertising. In this paper, we develop an MIV (marketing influential value) model to evaluate the influential strength and identify the influential bloggers in the blogosphere. We analyze three dimensions of blog characteristics (network-based, content-based, and activeness-based factors) and utilize an artificial neural network (ANN) to discover potential bloggers. Based on peer and official evaluations, the experimental results show that the proposed framework outperforms two social-network-based methods (out-degree and betweenness centrality algorithms) and two content-based mechanisms (review rating and popular author approaches). The proposed framework can be effectively applied to support marketers or advertisers in promoting their products or services.     

企业营销网络上的传播动力学特性

为了理解和解释企业营销网络上的传播机制,针对企业营销网络上的传播行为和网络拓扑结构特点,在SIR模型基础上,引入节点传播率指数和边权指数,建立企业营销网络上传播动力学模型,解析推导了企业营销网络上的传播临界值,并进行仿真分析。仿真结果表明,节点传播率指数和边权指数越大,传播临界值越小,越利于产品及产品相关信息的传播。最后,从减小传播临界值和提高实际传播率两个方面对企业营销提出了几点建议。     

The impact of study load on the dynamics of longitudinal email communications among students

With the advent of information technology, emails have gained wide acceptability among students as an asynchronous communication tool. According to the current pedagogy literature the overall trend of the use of email communication by university students has been increasing significantly since its inception, despite the rapid growth of the popularity and acceptability of other social mediums (e.g. Mobile phone and Facebook). In this study, we explore a longitudinal email communication network, which evolved under an increasing study load among 38 students throughout a university semester, using measures of social network analysis (SNA) and exponential random graph (ERG) models. This longitudinal network was divided into three waves, where each wave represents the portion of the complete longitudinal network that evolves between two consecutive observations. An increased study load was imposed through the assessment components of the course. SNA measures of degree centrality (i.e. the activity of an actor or actor popularity), betweenness centrality (i.e. the capacity to control the flow of information in a network), closeness centrality (i.e. reachable to other nodes) and reciprocity (i.e. tendency to make reciprocal links) are considered to explore this longitudinal network. ERG models are probabilistic models that are presented by locally determined explanatory variables and can effectively identify structural properties of networks. From the analysis of this email communication network, we notice that students' network positions and behaviours change with the changes in their study load. In particular, we find that (i) students make an increased number of email communications with the increase of study load; (ii) the email communication network become sparse with the increase of study load; and (iii) the 2-star parameter (a subset of three nodes in which one node is connected to each of the other two nodes) and the triangle parameter (a subset of three nodes in which each node is connected to the other two nodes) can effectively explain the formation of network in wave3; whereas, the 3-star parameter (a subset of four nodes in which one node is connected to each of other three nodes) can effectively explain the formation of network in wave1 and wave2. Interpretations of these findings for the monitoring of student behaviour in online learning environments, as well as the implications for the design of assessment and the use of asynchronous tools are discussed in this paper.     

Social capital expectation and usage of social media: the moderating role of social capital susceptibility

This study aims to identify the motivations of social media users who click ‘like’ to the post of their friends. We posit that this behaviour is not solely based on an instant feeling or reaction to a post, but a more complicated action that involves calculation and expectation of the future social media use. We first apply social capital theories to identify the types of expectations, and then differentiate these expectations based on the communication styles of social media where private and public relationships coexist. From these, we develop a social capital expectation matrix in the context of social media. In the research model, we discuss how these social capital expectations motivate people to use social media, including the moderating effects of social capital susceptibilities, based on expectancy theory of motivation. To validate our model, data collected from 291 social media users are analysed. This result confirms that people click likes to share their interests and display their network to others. Conversely, the relational dimensions of social capital including capital recompense and social inclusion exerted significant interaction effects only when they were considered along with capital susceptibilities.     

Cultivating Social Resources on Social Network Sites: Facebook Relationship Maintenance Behaviors and Their Role in Social Capital Processes

This study explores the relationship between perceived bridging social capital and specific Facebook‐enabled communication behaviors using survey data from a sample of U.S. adults (N=614). We explore the role of a specific set of Facebook behaviors that support relationship maintenance and assess the extent to which demographic variables, time on site, total and “actual” Facebook Friends, and this new measure (Facebook Relationship Maintenance Behaviors) predict bridging social capital. Drawing upon scholarship on social capital and relationship maintenance, we discuss the role of social grooming and attention‐signaling activities in shaping perceived access to resources in one's network as measured by bridging social capital.     

Social interaction and continuance intention in online auctions: A social capital perspective

This study explores how interaction within an online auction community affects online auction actor intention to continue trading with others. Adopting a social perspective drawing on social capital theory and IS literature, this study investigates how interactions among actors contribute to the creation and advancement of social capital. The analytical results demonstrate that the influence of user interaction on continuance intention in online auctions is mediated by the creation of various dimensions of social capital at the community level. Finally, the implications of the study findings are discussed.     

The effect of temporal psychological distance on reliance on word-of-mouth for information about destination image attributes

This study examines the effect of temporal psychological distance on travellers’ reliance on three types of word-of-mouth (WOM): traditional WOM (tWOM), social media WOM (SNS-WOM), and online review WOM (OR-WOM) in the search for information related to the relaxation, excitement, cost level, and safety destination image attributes. High and low temporal distance was manipulated using distances of 12 months and 2 months, respectively. A series of t-tests of 283 valid responses (155 and 128 for the 12-month and 2-month scenarios, respectively) shows a significant difference in reliance on tWOM when respondents sought safety attribute information, for SNS-WOM when respondents sought relaxation and safety attribute information, and for OR-WOM when respondents sought relaxation attribute information. Thus, this study shows that in terms of temporal distance, WOM is not a homogeneous block. They have sufficiently different characteristics (e.g. level of tie strength and synchronous/asynchronous modes), which, when they interact with the nature of the destination attributes, results in differing reliance on the three types of WOM under various temporal distances. This study thus contributes to construal level theory research and provides a better understanding of the different characteristics of the three types of WOM.     

企业营销复杂网络演化模型及其仿真

在对企业营销网络理解的基础上,将其抽象为复杂网络。分析了企业营销复杂网络的演化机制,建立了企业营销复杂网络演化模型,并对模型进行了仿真分析。结果表明企业营销复杂网络模型节点度分布、节点强度分布和边权分布均符合幂律分布,表明其能较好地拟合实际企业营销网络的拓扑结构特征。研究对于探讨企业营销网络的演化规律,对企业营销网络的建设和管理具有理论意义和实践价值。     

A videosharing social networking intervention for young adult cancer survivors

Clinicians interested in taking a proactive approach to healthy cancer survivorship might consider the use of a social networking and videosharing platform tailored specifically for young adult cancer survivors. This study examines six key factors that may influence a childhood cancer survivor’s participation in a social networking and videosharing intervention program tailored to their needs: (1) the individual’s social capital, defined as resources accessed by individuals through a broad range of social connections, (2) social support, (3) family interaction, (4) self-efficacy, (5) depression, and (6) self-reported quality of life. Fourteen healthy childhood cancer survivors participated in a social networking and videosharing intervention program, LIFECommunity, over a period of 6 months. Young adult cancer survivors with weak “bonding” social capital with other cancer survivors, little social support from friends and family, and lower family interaction participated in the social networking intervention more than those with stronger social capital and larger bases of support. The findings suggest that cancer survivors used the social network as a way to fulfill needs that were not being met in their “offline” lives. The study provides a deeper understanding of the factors that contribute to the success of social networking interventions for young cancer survivors.     

A comparison study of user behavior on Facebook and Gmail

Email is one of the most important communication media to date, and millions of Internet users around the world spend the bulk of their time writing and reading electronic messages. The growing popularity of Social Network Sites (SNS) as a communication medium motivated us to explore the relationship between user behavior on SNS and email. In this paper, we collected objective, privacy-preserved behavior data from participants that were both active Facebook and Gmail users. We show that a large proportion of social interactions still occur through email messages, while participants tend to be more emotional on Facebook. We found that producing more content on Facebook does not necessarily decrease or increase the production of emails. By utilizing the quantitative analysis of usage data instead of surveys, we show that user behavior is likely consistent across SNS and email in some aspects, for example, users with more Facebook friends seem to email to more people, Facebook and Gmail share similar trend of “happiness”.     

社交网络营销追踪

对社交网络营销效果追踪方面的研究尚处起步阶段.根据社交网络营销效果追踪的需求,设计了社交网络信息采集和数据处理平台.该平台使用爬虫技术的方式,在信息获取速度受限的前提下,尽可能多的获取信息.通过构建转发树的算法,得到社交网络营销追踪传播图.实验结果表明,平台自动获取所需求的数据并处理,绘制信息传播图,由此找到信息传播中的引爆点及其评论信息,即关系营销中重要关系节点及其反馈信息.平台还可以统计出互动用户的其他相关信息,便于社交网络营销效果的追踪.     

Social capital and access

Physical access to computers does not guarantee access to the information society. To help ensure that the first type of access translates into the second, it is necessary to pay attention to how computer and Internet use can enhance social capital. Drawing on examples from technology projects in India and other countries, this paper examines the concept of social capital and its relationship to information and communication technology, focusing on the role of both micro-level and macro-level social capital.     

Social network site use,mobile personal talk and social capital among teenagers

Social network sites (SNSs) and mobile phones are becoming increasingly important in teenagers’ lives. Using data collected from a nationally representative survey (N = 800), this study explores the variation of social capital by SNS adoption, different SNS activities, and mobile personal talk among teenagers. The results indicate that SNS adoption and mobile personal talk can not only enhance teenagers’ close ties with friends, but also jointly promote teenagers’ civic engagement. Among SNS users, mobile personal talk also increase teens’ network capital. Different SNS activities such as commenting on friend’s Facebook pictures and joining Facebook groups have different relationships with social capital, and such relationships are moderated by mobile personal talk.     

虚拟社会网络特征与公共危害信息的网络传播行为研究

首先给出了虚拟网络社会的概念,按照底层计算机网络拓扑结构的不同,将虚拟社会网络分类;其次分析虚拟社会网络的结构和特征,并应用社会资本观点对公共危害信息在虚拟社会服务网络传播的动机进行分析,最后从社会学的视角,提出了防治有害信息传播的治理策略。     

Web病毒式营销核心群体挖掘与推荐策略

Web病毒式营销已经成为电子商务领域中的重要营销策略, 核心群体在其中发挥着重要的作用。为了挖掘核心群体并对其进行商品推荐, 在Web客户信任网络(customer trust network, CTN)的基础上考虑了信任度、评价分数以及推荐次数等因素定义了影响度的概念, 提出了以影响度为基础的节点网络影响集的构建方法以及基于网络影响集的核心群体挖掘算法MCGNIS（mining core group based on network-influence set）, 并以挖掘出的核心群体为对象建立了基于网络影响集的推荐模型RCGNIS(recommending model for core group based on network-influence set）, 设计了相应的推荐算法来计算商品对核心群体的可推荐度。实验证明, 以节点网络影响集为基础挖掘出的核心群体在Web客户信任网络中具有较高的网络覆盖率（network-coverage, NC）, 推荐模型RCGNIS具有很好的推荐准确性, 同时又保持了推荐的多样性。     

Association of demographics,motives and intensity of using Social Networking Sites with the formation of bonding and bridging social capital in Pakistan

The objectives of this confirmatory study were to investigate the association of socio-economic demographics (age, education of respondent, gender, monthly family income, parentage education), motives (communication and information, self-actualization and outward looking) of using Social Networking Sites (SNSs) and attitudinal and behavior variable (intensity of using SNS, self-esteem, gratification with university life, duration of use, and number of ties) with the formation of bonding and bridging social capital. Total 461 students, aged 18–35 years filled the questionnaire, from randomly selected departments of University of the Punjab, Lahore, Pakistan. Regression analysis was used to assess the association among variables. The study indicated that Facebook is the most popular SNS among university students in Pakistan. Intensity of using SNS, duration of using SNSs, and motives of using SNSs were found to be positively associated with formation of bonding and bridging social capital. Self-esteem and gratifications with university life were found to be significant predictors in formation of bonding social capital only. The demographics variables (education, parentage education, monthly family income) had no influence on formation of both bonding and bridging social capital.     

The reciprocal effects of social network site use and the disposition for self-disclosure: A longitudinal study

Since the advent of social network sites (SNSs), scholars have critically discussed the psychological and societal implication of online self-disclosure. Does Facebook change our willingness to disclose personal information? The present study proposes that the use of SNSs and the psychological disposition for self-disclosure interact reciprocally: Individuals with a stronger disposition show a higher tendency to use SNSs (selection effect). At the same time, frequent SNS use increases the wish to self-disclose online, because self-disclosing behaviors are reinforced through social capital within the SNS environment (socialization effect). In a longitudinal panel study, 488 users of SNSs were surveyed twice in a 6 months interval. Data were analyzed using structure equation modeling. The proposed reciprocal effects of SNS activities and self-disclosure were supported by the data: The disposition for online self-disclosure had a positive longitudinal effect on SNS use which in turn positively influenced the disposition for online self-disclosure. Both effects were moderated by the amount of social capital users received as a consequence of their SNS use.     

Using Estimated Personality of Social Network Members for Finding Influential Nodes in Viral Marketing

Sending promotional messages to a few numbers of users in a social network can propagate a product through word of mouth. However, choosing users that receive promotional messages, in order to maximize propagation, is a considerable issue. These recipients are named “influential nodes.” To recognize influential nodes, according to the literature, criteria such as the relationships of network members or information shared by each member on a social network have been used. One of the effective factors in diffusion of messages is the personality characteristics of members. As far as we know, although this issue is considerable, so far it has not been applied in the previous studies. In this article, using the graph structure of social networks, two personality characteristics, openness and extroversion, are estimated for network members. Next, these two estimated characteristics together with other characteristics of social networks, are considered as the criteria of choosing influential nodes. To implement this process, the real coded genetic algorithm is used. The proposed method has been evaluated on a dataset including 1000 members of Twitter. Our results indicate that using the proposed method, compared with simple heuristic methods, can improve performance up to 37%.