• Social commerce development in emerging markets-taliem-ir

    Social commerce development in emerging markets

    تومان

    This study explores the development of a new form of social commerce in emerging markets from three interlocking aspects, namely, social (trust and familiarity), technical (governing form factor and technological utility), and socio-technical (perceived ease of use, perceived usefulness and word of mouth). As social commerce is proliferating and evolving across many emerging markets, we explore how these above-stated constructs manifest themselves in these markets. Our findings show the importance of governing form factors such as mobile system in the development of social commerce in emerging markets. Furthermore, familiarity and trust play a major role in mediating exchange between sellers and buyers and its positive effective in buyers’ perceived usefulness of each social commerce platform. Finally, Word of Mouth plays a vital role in building trust and helps in increasing buyer propensity and intention to search for products on these social commerce platforms.

     

  • Computational Models for Social Network Analysis[taliem.ir]

    Computational Models for Social Network Analysis: A Brief Survey

    تومان

    With the exponential growth of online social network services such as Facebook and Twitter, social networks and social medias become more and more important, directly influencing politics, economics, and our daily life. Mining big social networks aims to collect and analyze web-scale social data to reveal patterns of individual and group behaviors. It is an inherently interdisciplinary academic field which emerged from  sociology, psychology, statistics, and graph theory. In this article, I briefly survey recent progress on social network mining with an emphasis on understanding the interactions among users in the large dynamic social networks. I will start with some basic knowledge for social network analysis, including methodologies and tools for macro-level, meso-level and microlevel social network analysis. Then I will give an overall  roadmap of social network mining. After that, I will describe methodologies for modeling user behavior including state-of-the-art methods forlearning user profiles, and introduce recent progress on modeling dynamics of user behaviors using deep learning. Then I will present models and algorithms for quantitative analysis on social interactions including homophily and social influence.Finally, I will introduce network structure model including social group formation, and network topology generation. We will introduce recent developed network embedding algorithms for modeling social networks with the embedding techniques. Finally, I will use several concrete examples from Alibaba, the largest online  shopping website in the world, and WeChat, the largest social messaging service in China, to explain how online social networks influence our offline world.

  • Management perception[taliem.ir]

    Management perception of introducing social networking sites as a knowledge management tool in higher education A case study

    تومان

    Purpose – The purpose of this paper is to present a study of the understanding and usage of social  networking sites (SNS) as a knowledge management (KM) tool in knowledge-intensive enterprises .Design/methodology/approach – In terms of research approach, the study has taken an interpretitivist framework, using a higher education (HE) institution as the case-study, which is characterised by the need to generate process, share and use knowledge on a daily basis in order to remain competitive. The case study was analysed using qualitative research methodology, composed of interviews and utilised narrative analysis as a means of data analysis, thus deriving a characterisation of understandings, perceptions and acceptance of SNS as a KM tool .Findings – The study provides evidence that even in HE, where it is generally acknowledged that there is a need to adequately capture, store, share and disseminate knowledge, as this can lead to greater innovation, creativity and productivity, participants were suspicious of the nature of the technology and the fact that it could intertwine their professional and social life. As a result, they were not prepared to invest the relatively high effort required in employing SNS as a KM tool as they also have difficulty in establishing the added value. Consequently, in order to employ SNS for KM purposes cultural ,behavioural and organisational issues need to be tackled before even considering technical issues. Originality/value – The paper provides an insight into KM and social networking in HE. This also highlights issue for international HE.

  • Social media Get serious! Understanding the.[taliem.ir]

    Social media? Get serious! Understanding the functional building blocks of social media

    تومان

    Traditionally, consumers used the Internet to simply expend content: they read it, they watched it, and they used it to buy products and services. Increasingly ,however, consumers are utilizing platforms–—such as  content sharing sites, blogs, social networking, and wikis–—to create, modify, share, and discuss Internet content. This represents the social media phenomenon, which can now significantly impact a firm’s reputation, sales, and even survival. Yet, many executives eschew or ignore this form of media because they don’t understand what it is, the various forms it can take, and how to engage with it and learn. In response, we present a framework that defines social media by using seven functional building blocks: identity,  conversations, sharing, presence, relationships, reputation, and groups. As different social media activities are defined by the extent to which they focus on some or all of these blocks ,we explain the implications that each block can have for how firms should engage with social media. To conclude, we present a number of recommendations regarding how firms should develop strategies for monitoring, understanding, and responding to different social media activities.

  • Social networking on the[taliem.ir]

    Social networking on the semantic web

    تومان

    Purpose – Aims to investigate the way that the semantic web is being used to represent and process social network information. Design/methodology/approach – The Swoogle semantic web search engine was used to construct several large data sets of Resource Description Framework (RDF) documents with social  network information that were encoded using the “Friend of a Friend” (FOAF) ontology. The datasets were analyzed to discover how FOAF is being used and investigate the kinds of social networks found on the web. Findings – The FOAF ontology is the most widely used domain ontology on the semantic web. People are using it in an open and extensible manner by defining new classes and properties to use with FOAF. Research limitations/implications – RDF data was only obtained from public RDF documents published on the web. Some RDF FOAF data may be unavailable because it is behind firewalls, on intranets or stored in private databases. The ways in which the semantic web languages RDF and OWL are being used (and abused) are dynamic and still evolving. A similar study done two years from now may show very different results. Originality/value – This paper describes how social networks are being encoded and used on the world wide web in the form of RDF documents and the FOAF ontology. It provides data on large social networks as well as insights on how the semantic web is being used in 2005 .

  • Trustworthiness Management in the Social[taliem.ir]

    Trustworthiness Management in the Social Internet of Things

    تومان

    The integration of social networking concepts into the Internet of things has led to the Social Internet of  Things (SIoT) paradigm, according to which objects are capable of establishing social relationships in an  autonomous way with respect to their owners with the benefits of improving the network scalability in  information/service discovery. Within this scenario, we focus on the problem of understanding how the  information provided by members of the social IoT has to be processed so as to build a reliable system on the basis of the behavior of the objects. We define two models for trustworthiness management starting  from the solutions proposed for P2P and social networks. In the subjective model each node computes the trustworthiness of its friends on the basis of its own experience and on the opinion of the friends in common with the potential service providers. In the objective model, the information about each node is distributed and stored making use of a distributed hash table structure so that any node can make use of the same information. Simulations show how the proposed models can effectively isolate almost any malicious nodes in the network at the expenses of an increase in the network traffic for feedback exchange.

  • Trustworthiness Management in the Social[taliem.ir]

    Trustworthiness Management in the Social Internet of Things

    تومان

    The integration of social networking concepts into the Internet of things has led to the Social Internet of  Things (SIoT) paradigm, according to which objects are capable of establishing social relationships in an  autonomous way with respect to their owners with the benefits of improving the network scalability in  information/service discovery. Within this scenario, we focus on the problem of understanding how the information provided by members of the social IoT has to be processed so as to build a reliable system on the basis of the behavior of the objects. We define two models for trustworthiness management starting from the solutions proposed for P2P and social networks. In the subjective model each node computes the trustworthiness of its friends on the basis of its own experience and on the opinion of the friends in common with the potential service providers. In the objective model, the information about each node is distributed and stored making use of a distributed hash table structure so that any node can make use of the same  information. Simulations show how the proposed models can effectively isolate almost any malicious nodes in the network at the expenses of an increase in the network traffic for feedback exchange.