A system and method that uses internet content and/or content metadata as a means to establish social networks. Examples include linking internet users, searchers, viewers and/or listeners of the same and/or similar internet content to each other via a platform that enables any of the following in n-dimensional environments: social networking, communications, sharing, e-commerce, advertising, search, hosting and registry services, push and pull applications, anonymous communications, and rich presence.

Using internet content as a means to establish live social networks by linking internet users to each other who are simultaneously engaged in the same and/or similar content

https://research.vu.nl/ws/files/2241859/197060.pdf

Flink: Semantic Web technology for the extraction and analysis of social networks

A formal, web-based representation of social networks is both a necessity in terms of infrastructure as well as a prominent application for the Semantic Web. In this paper we present three advances in exploiting the opportunity of semantically-enriched network data: (1) an ontology for the representation of social networks and relationships (2) a hybrid system for online data acquisition that combines traditional web mining techniques with the collection of Semantic Web data (2) a case study highlighting some of the possible analysis of this data using methods from Social Network Analysis, the branch of sociology concerned with relational data.

Social Networks and the Semantic Web

A critical factor in work group coordination, communication has been studied extensively. Yet, we are missing objective evidence of the relationship between successful coordination outcome and communication structures. Using data from IBM's Jazz™ project, we study communication structures of development teams with high coordination needs. We conceptualize coordination outcome by the result of their code integration build processes (successful or failed) and study team communication structures with social network measures. Our results indicate that developer communication plays an important role in the quality of software integrations. Although we found that no individual measure could indicate whether a build will fail or succeed, we leveraged the combination of communication structure measures into a predictive model that indicates whether an integration will fail. When used for five project teams, our predictive model yielded recall values between 55% and 75%, and precision values between 50% to 76%.

Predicting build failures using social network analysis on developer communication

Management of the enterprise architecture has become increasingly recognized as a crucial part of both business and IT management. Still, a common understanding and methodological consistency seems far from being developed. Acknowledging the significant role of research in moving the development process along, this article employs different bibliometric methods, complemented by an extensive qualitative interpretation of the research field, to provide a unique overview of the enterprise architecture literature. After answering our research questions about the collaboration via co-authorships, the intellectual structure of the research field and its most influential works, and the principal themes of research, we propose an agenda for future research based on the findings from the above analyses and their comparison to empirical insights from the literature. In particular, our study finds a considerable degree of co-authorship clustering and a positive impact of the extent of co-authorship on the diffusion of works on enterprise architecture. In addition, this article identifies three major research streams and shows that research to date has revolved around specific themes, while some of high practical relevance receive minor attention. Hence, the contribution of our study is manifold and offers support for researchers and practitioners alike.

/pdf/an-exploration-of-enterprise-architecture-research-4v89t1o8he.pdf

An Exploration of Enterprise Architecture Research

Collaborative Innovation Networks (COINs) are groups of self-motivated individuals from various parts of an organization or from multiple organizations, empowered by the Internet, who work together on a new idea, driven by a common vision. In this paper we report first results of a project that examines innovation networks by analyzing the e-mail archives of some W3C (WWW consortium) working groups. These groups exhibit ideal characteristics for our purpose, as they form truly global networks working together over the Internet to develop next generation technologies. We first describe the software tools we developed to visualize the temporal communication flow, which represent communication patterns as directed acyclic graphs, We then show initial results, which revealed significant variations between the communication patterns and network structures of the different groups., We were also able to identify distinctive communication patterns among group leaders, both those who were officially appointed and other who were assuming unofficial coordinating roles.

/pdf/visualization-of-communication-patterns-in-collaborative-3b7jxuw2d6.pdf

Visualization of Communication Patterns in Collaborative Innovation Networks - Analysis of Some W3C Working Groups

iQuest is a novel software system to improve understanding of organizational phenomena with greater precision, clarity, and granularity than has previously been possible. It permits to gain new insights into organizational behavior, addressing issues such as tracking information while respecting privacy, comparing different interaction channels, network membership, and correlating organizational performance and creativity. It extends automatic visualization of social networks by mining communication archives such as e-mail and blogs through including analysis of the contents of those archives.

/pdf/analyzing-actors-and-their-discussion-topics-by-semantic-5ds3k1o945.pdf

Yan Zhao

Papers

Visualization of Communication Patterns in Collaborative Innovation Networks - Analysis of Some W3C Working Groups

Analyzing Actors and Their Discussion Topics by Semantic Social Network Analysis