Showing papers by "Sameep Mehta published in 2010"

A study of rumor control strategies on social networks

Abstract: In this paper we study and evaluate rumor-like methods for combating the spread of rumors on a social network. We model rumor spread as a diffusion process on a network and suggest the use of an "anti-rumor" process similar to the rumor process. We study two natural models by which these anti-rumors may arise. The main metrics we study are the belief time, i.e., the duration for which a person believes the rumor to be true and point of decline, i.e., point after which anti-rumor process dominates the rumor process. We evaluate our methods by simulating rumor spread and anti-rumor spread on a data set derived from the social networking site Twitter and on a synthetic network generated according to the Watts and Strogatz model. We find that the lifetime of a rumor increases if the delay in detecting it increases, and the relationship is at least linear. Further our findings show that coupling the detection and anti-rumor strategy by embedding agents in the network, we call them beacons, is an effective means of fighting the spread of rumor, even if these beacons do not share information.

Outcome aware ranking in interaction networks

Abstract: In this paper, we present a novel ranking technique that we developed in the context of an application that arose in a Service Delivery setting. We consider the problem of ranking agents of a service organization. The service agents typically need to interact with other service agents to accomplish the end goal of resolving customer requests. Their ranking needs to take into account two aspects: firstly, their importance in the network structure that arises as a result of their interactions, and secondly, the value generated by the interactions involving them. We highlight several other applications which have the common theme of ranking the participants of a value creation process based on the network structure of their interactions and the value generated by their interactions. We formally present the problem and describe the modeling technique which enables us to encode the value of interaction in the graph. Our ranking algorithm is based on extension of eigen value methods. We present experimental results on real-life, public domain datasets from the Internet Movie DataBase. This makes our experiments replicable and verifiable.

Methods and arrangements for prioritizing service restoration activities in the event of a catastrophic failure

Abstract: Methods and arrangements for prioritizing customer service restoration, in the event of service failure or compromise such that any adverse effect of the service disruption on the customer is minimized, the perceived drop in quality of service, if any, is minimized and timely and efficient resource reallocation for service restoration is achieved. Input data relating to customer service protocols is assimilated. A service restoration order is implemented responsive to a service disruption and based on the assimilated input data. This implementing includes determining bufferable and non-bufferable services, postponing restoration of the bufferable services, and determining an order of priority of the non-bufferable services.