Networks are used to represent interactions in a wide variety of fields, like biology, sociology, chemistry, and more. They have a great deal of salient information contained in their structures, which have a variety ...Networks are used to represent interactions in a wide variety of fields, like biology, sociology, chemistry, and more. They have a great deal of salient information contained in their structures, which have a variety of applications. One of the important topics of network analysis is finding influential nodes. These nodes are of two kinds —leader nodes and bridge nodes. In this study, we propose an algorithm to find strong leaders in a network based on a revision of neighborhood similarity. This leadership detection is combined with a neighborhood intersection clustering algorithm to produce high quality communities for various networks. We also delve into the structure of a new network, the Houghton College Twitter network, and examine the discovered leaders and their respective followers in more depth than which is frequently attempted for a network of its size. The results of the observations on this and other networks demonstrate that the community partitions found by this algorithm are very similar to those of ground truth communities.展开更多
This paper empirically investigates into the business performance benefit that lead users or opinion leaders among small business owners draw from their higher involvement in management accounting or marketing topics....This paper empirically investigates into the business performance benefit that lead users or opinion leaders among small business owners draw from their higher involvement in management accounting or marketing topics. This work also contributes to a better identification of network members’ roles solely through their ties between each other. Indeed, lead users and opinion leaders can be differentiated by a higher degree centrality in comparison to their peers. However, being an opinion leader or a lead user does not yield a measurable business benefit to the small businesses studied in this sample.展开更多
文摘Networks are used to represent interactions in a wide variety of fields, like biology, sociology, chemistry, and more. They have a great deal of salient information contained in their structures, which have a variety of applications. One of the important topics of network analysis is finding influential nodes. These nodes are of two kinds —leader nodes and bridge nodes. In this study, we propose an algorithm to find strong leaders in a network based on a revision of neighborhood similarity. This leadership detection is combined with a neighborhood intersection clustering algorithm to produce high quality communities for various networks. We also delve into the structure of a new network, the Houghton College Twitter network, and examine the discovered leaders and their respective followers in more depth than which is frequently attempted for a network of its size. The results of the observations on this and other networks demonstrate that the community partitions found by this algorithm are very similar to those of ground truth communities.
文摘This paper empirically investigates into the business performance benefit that lead users or opinion leaders among small business owners draw from their higher involvement in management accounting or marketing topics. This work also contributes to a better identification of network members’ roles solely through their ties between each other. Indeed, lead users and opinion leaders can be differentiated by a higher degree centrality in comparison to their peers. However, being an opinion leader or a lead user does not yield a measurable business benefit to the small businesses studied in this sample.
