Social network analysis of B2B networks

The volume of information readily available in the EMarketplace is massive.Business-to-business (B2B) users, for instance, have an extensive chain of business relationships that have immensely generated a large volume of information. Although this raises problems of information overload, the data is embedded with rich and valuable information, such as internal structure and social networks.While other research focuses on discovering properties of B2C, C2C and P2P networks, there only exists limited work on B2B, attributable to the high complexity of the B2B structure.This paper presents a statistical analysis of B2B networks that amasses dispersed users' social relationships using a social network analysis technique.The investigation performed found that B2B networks are small-world, and thus follow a power-law distribution. The analysis also proved that B2B networks hold stable community structures

SOCIAL NETWORK ANALYSIS OF B2B NETWORKS

The volume of information readily available in the E-Marketplace is massive. Business-to-business (B2B) users, for instance, have an extensive chain of business relationships that have immensely generated a large volume of information. Although this raises problems of information overload, the data is embedded with rich and valuable information, such as internal structure and social networks. While other research focuses on discovering properties of B2C, C2C and P2P networks, there only exists limited work on B2B, attributable to the high complexity of the B2B structure. This paper presents a statistical analysis of B2B networks that amasses dispersed users' social relationships using a social network analysis technique. The investigation performed found that B2B networks are small-world, and thus follow a power-law distribution. The analysis also proved that B2B networks hold stable community structures.Malaysia Council of Trust for the Bumiputer

Study of Communication Network Travel-Related eWOM on Instagram Social Media

The research is about analysis of communication network to travel-related EWOM IN social media Instagram on account  @exploremalang which researcher want to know how characteristic of network system formed and the usual messages in travel-related EWOM on account @exploremalang in Instagram. Paradigm which used is Post-positivism by unobtrusive methods data in collection data. The research used communication network analysis method and content analysis to know content of messages common said by actors, and how intimacy actors in the form of a travel-related eWOM.  Result of the research found structure of communication network in the form of global network Radial personal network from four photos which selected by researcher. Measurement showed cohesiveness in this network is low. Measurement of degree, betweeness and closeness dominated by actors who often mentions other actors. Then, obtained interlocking personal network click formed. Meanwhile structure of network, researcher also found sixth characteristic of travel-related EWOM.

Social Network Analysis of Online Marketplaces

This paper presents a preliminary effort on visualization and analysis of social networks for online marketplaces. We use one of the most popular e-business models, eBay, as a case study. By extracting relevant data, we generate tree structure displays using ‘Prefuse ’ interactive visualization toolkit, and study the social interaction among sellers and buyers, across geographical boundaries. We also illustrate how this study can improvise our understanding of online customer interaction patterns. Such an analysis could lead to possible enhancements to the current e-business models. 1