A Dynamic Trust Relations-Based Friend Recommendation Algorithm in Social Network Systems

A discovered algorithm based on the dynamic trust relations of users in a social network system (SNS) was proposed aiming at getting useful information more efficiently in an SNS. The proposed dynamic model combined the interests and trust relations of users to explore their good friends for recommendations. First, the network based on the interests and trust relations of users was set up. Second, the temporal factor was added to the model, then a dynamic model of the degree of the interest and trust relations of the users was calculated. Lastly, the similarities among the users were measured via this dynamic model, and the recommendation list of good friends was achieved. Results showed that the proposed algorithm effectively described the changes in the interest similarities and trust relations of users with time, and the recommended result was more accurate and effective than the traditional ones

Consumer participation and the trust transference process in using online recommendation agents

Online product recommendation agents (hereafter RAs) can provide important benefits to consumers. But whether consumers trust RAs and integrate an RA\u27s recommendations into their product choices has not yet been examined. Nor has there been research on whether different levels of consumer participation in using RAs lead to different levels of trust in the RA. Using an experimental design that combined the benefits of a field study with those of a lab study, active consumer participation in using an RA was found to have increased consumers\u27 trust in the RA, which in turn increased intentions to purchase based on the RA\u27s recommendations. The study also proposed and found support for a trust transference process, hitherto not tested in the RA context, wherein trust in the website was a key driver for trust in its RA and the RA\u27s recommendations. These findings extend the extant literature on RAs as well as research in offline contexts on consumer participation and the trust transference process. Managerial implications and directions for future research are also provided

Individual level culture influence on online consumer iTrust aspects towards purchase intention across cultures: A S-O-R model

© 2015 Inderscience Enterprises Ltd. Building trust and understanding its relationship with online purchasing decisions is important to business-to-consumer (B2C) e-commerce firms seeking to extend their consumers reach globally. Based on the Stimulus- Organism-Response (S-O-R) model, this paper examines the moderating role of culture on the relationship between B2C web design (web accessibility, visual appearance and social networking services (SNS)) and interpersonal trust (iTrust), cognitive and affect-based trust that trigger online purchasing intentions. Motivation of this study includes, testing and comparing individual consumer level cultural (individualism and uncertainty avoidance) values as moderators in our research model across two different societies (Australia and Pakistan). The data of the survey were analysed using structural equation modelling-partial least square (SEM-PLS) approach. The results highlight the need to consider cultural differences when identifying the mix of web design strategies to employ in B2C e-commerce websites, not only at the country level but also in one culturally diverse country such as Australia

Professional online networking : investigating the technological and the human side of networking with professional social networking sites

Professional social networking sites (SNS) have become a vital part of modern days professional lives. They are a convenient way to receive information about job offers, work-related content, and to connect with other professionals independent of time and space. Research in the field of social capital has shown that a network of people can give access to information, influence, and solidarity which positively affect both subjective and objective career outcomes. Moreover, research has shown that a diverse network is most beneficial as it gives access to non-redundant information, new perspectives, and new ideas. Yet, most professional SNS users are mainly connected with others from their direct work environments such as colleagues and university friends. For one thing, this is because of the homophily principle which states that people tend to surround themselves with others who are similar to them. On the other hand, contact recommender systems of professional SNS support connecting with similar others as contact recommendations are usually based on similarity. The cumulative dissertation, therefore, was set out to investigate the technological and the human side of professional online networking to gain evidence on how to encourage professional SNS users to build more diverse business networks. The dissertation consists of four research articles answering the following four research questions: 1. Is there a difference between offline and online professional networking in terms of intensity and in terms of influence factors? 2. How do basic technological features and functions (e.g. diverse contact recommendations) influence professional online networking? 3. How do different information designs of contact recommendations influence professional online networking? 4. How does diverse online networking influence peoples social identification with their online business networks? In summary, the four research articles show that peoples online networking is mainly driven by cognitive factors, more specifically, peoples knowledge about the benefits of (diverse) networking. When people know about the benefits of networking and the benefits of diverse networking, they network more and more diverse. This can be addressed in the design of contact recommendations by displaying an explanation why someone is recommended thereby hinting at the benefits of networking in general and at the benefits of diversity. Moreover, this can be addressed by presenting contact recommendations emphasizing dissimilarity information in contrast to similarity information. Both different types of explanations and different types of information weaken the homophily principle and encourage people to network more diverse. Besides, basic technological functions influence online networking. When people are presented with a more diverse set of contact recommendations to choose from, they do not network less but consequently, end up with a more diverse business network. Furthermore, the negative affective influence of anxiety towards unknown people is different for offline than for online networking. In line with the social compensation hypothesis, in online settings, the negative influence is weaker than it is in offline settings. When only looking at online settings we see that higher levels of anxiety still reduce the number of people connected with but not the diversity of the resulting networks. Hence, people do not feel less anxiety when connecting with similar others than when connecting with dissimilar others. Finally, returning to the side of the user we see that more diverse online networking leads to a reduction of social identification with peoples online business networks. Diverse online networking reduces social identification with the network and as a result the willingness to support the network. Hence, diverse online networking compromises the benefits a network provides. Yet, in the absence of similarity, there is also evidence that people attribute others in their online networks with characteristics of their own to perceive them as similar. Shared characteristics function as a reason to identify and compensate for the lack of formal similarity when business networks become more diverse. Moreover, the specific features and functions of professional SNS besides contact recommendations can compensate for the lack of identification.Berufliche Social Networking Sites (SNS) sind aus dem modernen Berufsleben nicht mehr wegzudenken. Sie sind eine bequeme Möglichkeit, Informationen über Stellenangebote und arbeitsbezogene Inhalte zu erhalten und sich mit Fachleuten unabhängig von Zeit und Raum zu vernetzen. Forschung auf dem Gebiet des sozialen Kapitals hat gezeigt, dass ein Netzwerk Zugang zu Informationen, Einfluss und Solidarität bietet, was sowohl subjektive als auch objektive berufliche Ergebnisse positiv beeinflusst. Darüber hinaus hat die Forschung gezeigt, dass ein diverses Netzwerk am vorteilhaftesten ist, da es den Zugang zu nicht redundanten Informationen, neuen Perspektiven und neuen Ideen ermöglicht. Dennoch sind die meisten Nutzer*innen auf beruflichen SNS hauptsächlich mit anderen aus ihrem direkten Arbeitsumfeld, wie zum Beispiel mit Kolleg*innen und Freund*innen von der Universität vernetzt. Dies liegt zum einen am Homophilie-Prinzip, das besagt, dass Menschen dazu neigen, sich mit Personen zu umgeben, die ihnen ähnlich sind. Zum anderen unterstützen Kontaktempfehlungssysteme auf beruflichen SNS das Vernetzen mit ähnlichen Personen, da Kontaktempfehlungen in der Regel auf Ähnlichkeit basieren. Die kumulative Dissertation untersuchte daher die technologische und die menschliche Seite des beruflichen online Networkings, um Erkenntnisse darüber zu gewinnen, wie Nutzer*innen von beruflichen SNS dazu ermutigt werden können, diverse berufliche Netzwerke aufzubauen. Die Dissertation besteht aus vier Forschungsartikeln, die die folgenden vier Forschungsfragen beantworten: 1. Gibt es einen Unterschied zwischen offline und online beruflichem Networking in Bezug auf die Intensität und in Bezug auf die Einflussfaktoren? 2. Wie beeinflussen grundlegende technologische Merkmale und Funktionen (z.B. diverse Kontaktempfehlungen) das berufliche online Networking? 3. Wie beeinflussen unterschiedliche Informationsdesigns von Kontaktempfehlungen das berufliche online Networking? 4. Wie beeinflusst diverses online Networking die soziale Identifikation der Menschen mit ihren beruflichen online Netzwerken? Zusammenfassend zeigen die vier Artikel, dass online Networking hauptsächlich durch kognitive Faktoren gelenkt wird, genauer gesagt durch das Wissen um die Vorteile von Networking. Wenn Menschen die Vorteile des Networkings und die Vorteile des diversen Networkings kennen, vernetzen sie sich mit mehr Personen und diverser. Dem kann bei der Gestaltung von Kontaktempfehlungen dadurch Rechnung getragen werden, dass eine Erklärung angezeigt wird, warum jemand empfohlen wird. Darüber hinaus kann dem Einfluss des Wissens durch die Auswahl der Informationen von Kontaktempfehlungen Rechnung getragen werden. Bei der Präsentation von Kontaktempfehlungen können Informationen zu Unterschiedlichkeiten im Gegensatz zu Informationen zu Ähnlichkeiten betont werden. Sowohl unterschiedliche Arten von Erklärungen als auch unterschiedliche Arten von Informationen schwächen das Homophilie-Prinzip und ermutigen Nutzer*innen dazu, sich diverser zu vernetzen. Außerdem beeinflussen grundlegende technologische Funktionen das online Networking. Wird ein diverses Set an Kontaktempfehlungen zur Auswahl angeboten, vernetzen sich Nutzer*innen nicht mit weniger Menschen, sondern erhalten ein diverseres Netzwerk. Darüber hinaus ist der negative affektive Einfluss der Angst gegenüber unbekannten Personen beim offline Networking anders als beim online Networking. In Übereinstimmung mit der Hypothese der sozialen Kompensation ist der negative Einfluss in online Umgebungen schwächer als in offline Umgebungen. Wenn wir nur online Networking betrachten, stellen wir fest, dass ein höheres Level an Angst zwar die Größe allerdings nicht die Diversität des entstandenen Netzwerks reduziert. Daraus folgt, dass Menschen nicht weniger Angst empfinden, wenn sie sich mit ähnlichen Personen vernetzen als wenn sie sich mit unähnlichen Personen vernetzen. Wenn wir schließlich auf die Seite der Nutzer*innen zurückkehren, sehen wir, dass diverses online Networking zu einer Verringerung der sozialen Identifikation mit dem beruflichen online Netzwerk führt. Diverses online Networking reduziert die soziale Identifikation mit dem Netzwerk und infolgedessen die Bereitschaft das Netzwerk zu unterstützen. Daher beeinträchtigt diverses online Networking die Vorteile, die ein Netzwerk bietet. Bei fehlender Ähnlichkeit gibt es jedoch auch Hinweise darauf, dass Menschen anderen in ihrem online Netzwerk eigene Eigenschaften und Merkmale zuschreiben, um sie als ähnlich wahrzunehmen. Gemeinsame Eigenschaften und Merkmale dienen als Grundlage, sich mit anderen Personen zu identifizieren und den Mangel an formalen Ähnlichkeiten auszugleichen, wenn berufliche Netzwerke stets diverser werden. Darüber hinaus gleichen auch die spezifischen Merkmale und Funktionen beruflicher SNS, die neben Kontaktempfehlungen existieren, einen Mangel an Identifikation aus

A social commerce investigation of the role of trust in a social networking site on purchase intentions

Trust is a crucial issue in online shopping environments, but it is more important in social commerce platforms due to the salient role of peer-generated contents. This article investigates the relationship between trust in social commerce and purchase intentions and describes a mechanism to explain this relationship. We propose a main and two alternative models by drawing on three concepts: social commerce information seeking, familiarity with the platform, and social presence. The models clarify the mechanisms through which trust, familiarity, social presence, and social commerce information seeking influence behavioral intentions on social commerce platforms. Findings from a survey of Facebook users indicate that trust in a social networking site (SNS) increases information seeking which in turn increases familiarity with the platform and the sense of social presence. Moreover, familiarity and social presence increase purchases intentions. Findings indicate that the main model fits the data better than the alternative ones. Theoretical and managerial implications are discussed

A Systematic Review of Social Networks Research in Information Systems: Building a Foundation for Exciting Future Research

Social networking applications such as blogs, instant messengers, podcasts, social networking websites (e.g., Renren in China, Vkontakte in Russia, Facebook), professional networking websites (e.g., LinkedIn), Twitter, and virtual worlds (e.g., Second Life) have become increasingly popular in the last few years. Because these applications have substantial implications for users, organizations, and society, social networks (SNs) have gained attention from information systems (IS) researchers and grown steadily as a research area since 2004. However, to organize the accumulated research and encourage researchers to examine new and pressing issues in SNs, available knowledge needs to be synthesized and research gaps need to be addressed (Bandara et al., 2011). Therefore, we systematically reviewed publications about SNs published in major IS journals between January 2004 and August 2013 and, in this paper, overview the state of IS research regarding SNs. We show the evolution of the existing IS research on SNs to build a common nomenclature and taxonomy for this area of research, to identify theories used, and to provide a useful roadmap for future research in this area

INFLUENTIAL FACTORS OF RECOMMENDATION BEHAVIOUR IN SOCIAL NETWORK SITES - AN EMPIRICAL ANALYSIS

This paper analyzes influential factors of recommendation behaviour in social network sites (SNSs). Extant research on both SNSs and electronic word of mouth (eWOM) has given insufficient attention to SNSs as a potential eWOM channel. Considering the specificities of SNSs, this paper distinguishes implicit and explicit recommendation behaviour. Drawing upon research on eWOM, SNSs, and knowledge exchange, influential factors of implicit and explicit recommendation behaviour are identified. A theoretical model explaining why SNS users (do not) engage in implicit and explicit recommendation behaviour is developed. Structural equation modeling (SEM) is used for hypothesis testing. Data was collected via an online survey from 832 SNS users. The empirical results show a positive impact of reciprocity on both implicit and explicit recommendation behaviour, a negative impact of fear of producing spam on implicit recommendation behaviour, and a positive impact of both implicit recommendation behaviour and the perceived value of the recommended product on explicit recommendation behaviour