Social PLM, Graphs and Organizational Overlap

Social PLM, Graphs and Organizational Overlap

Social tools are capturing lots of noise and making real impact these days. After initial hype of MySpace and early days of Facebook, social networks is getting down to real business, profit and smart technology. LinkedIn engineering publication earlier today speaks about some smart engineering work done by LinkedIn engineers analyzing data about people connections. Navigate to the following link to read Organizational Overlap on Social Networks and its Applications. I found some facts from this article quite interesting. One of them related to the ability of connection identification.

A basic problem in network analysis is predicting links for partially observed networks, that is, given a snapshot of connections at time t, can we predict links at time t+1. On any online social network, two members might know each other, but may not have established a connection on the site. Link prediction and recommendations help address this problem and create a more complete social graph to improve user involvement.

Another interesting use is identification of communities.

The organizational overlap model also works well for detecting communities within an organization. It is usually hard to evaluate the quality of communities because of a lack of ground truth. We used an indirect method to evaluate the quality: intuitively, the speed of information propagation should be faster within a community, so we measured the quality of detected communities by the speed of information propagation within it.

The problem of identification of communities can be interesting in the context of introducing of social network in product development organization and actually in any enterprise organization. The communication patterns in existing organization is mostly driven by emails these days. Social networks are just establishing themselves and engineering is probably not the first place where they start. However, the ability to capture communication relationships between engineers can help to identify knowledge gaps and efficiency problems.

What is my conclusion? The combination of data networks and communication network can bring lots of new opportunities in product development. At the time, companies are scratching their heads trying to understand where next cost saving will come from, the answers are probably deep in the roots of social product networks. Just my thoughts…

Best, Oleg


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