Master's Thesis Nr. 101
نویسنده
چکیده
If you take meetings, instant messaging, emails and calls out of your working day there is a fair chance that the remaining work-related communication is relatively small. Most of people’s daily lives is interacting with the social network at the office, engaging with people and using relationships to drive innovation and results. Most individuals would attest to having a good understanding of their network, knowing their key counterparts and using their connections wisely. However, people can not verify if that is correct. In this work, we present a novel way of aggregating employees social interactions at work and building their social graph. Key contributions include the development of an importance algorithm used throughout the application to access peers business relation and filter the best ones, determine communities of practice and find critical hotspots which could improve performance and collaboration. The interactions across the hierarchy are modeled to reveal insights into divisional-based communication patterns. Different methods are discussed how to get the best referral to a new business contact inside the company as well as outside it, across the organizational boundaries.
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