Mechanism design for finding experts using locally constructed social referral web

Abstract

Abstract-In this work, we address the problem of distributed expert finding using chains of social referrals and profile matching with only local information in online social networks. By assuming that users are selfish, rational, and have privately known cost of participating in the referrals, we design a novel truthful efficient mechanism in which an expert-finding query will be relayed by intermediate users. When receiving a referral request, a participant will locally choose among her neighbors some user to relay the request. In our mechanism, several closely coupled methods are carefully designed to improve the performance of distributed search, including, profile matching, social acquaintance prediction, score function for locally choosing relay neighbors, and budget estimation. We conduct extensive experiments on several datasets of online social networks. The extensive study of our mechanism shows that the success rate of our mechanism is about 90% in finding closely matched experts using only local search and limited budget, which significantly improves the previously best rate 20%. The overall cost of finding an expert by our truthful mechanism is about 20% of the untruthful methods, e.g.. the method that always selects high-degree neighbors. The median length of social referral chains is 6 using our localized search decision, which surprisingly matches the well-known small-world phenomenon of global social structures.

Investigating the Expertise Indicators of Vulnerability Discovery Professionals

“…They rely mostly on referrals from experts to delegate a task to another expert in her network. In the same context, Zhang et al proposed a mechanism for finding experts by a referral chain from the initiator to the expert [35]. Similarly, the work of Pushpa et al has addressed searching for expertise in a network of co-authorship where a query to find an expert is seen 5 www.upwork.com/i/how-it-works/client/ by an agent that manages the expertise model of the users.…”

Truthful Auction Mechanisms with Performance Guarantee in Secondary Spectrum Markets

“…In recent years, various auction models have been successfully designed in the communication and networking field [16], [27], [36], [37]. For instance, Yang et al proposed TASC [36], a double auction scheme for the cooperative communication scenario.…”

iASK: a distributed Q&A system incorporating social community and global collective intelligence

“…Recently, many research efforts began to study socialbased Q&A systems [6,7,8,9,10,11,12]. The systems in [6,7] are based on broadcasting.…”

“…Centralized methods have problems of single point of failure, higher bandwidth and server maintenance costs [10]. Zhang et al [12] proposed an expert finding mechanism coupling with profile matching and social acquaintance prediction methods in order to forward referral requests through social links to experts. SOS [10] is a distributed Q&A system based on a social network that forwards questions in a distributed manner in an asker's social network, and uses knowledge engineering techniques to find the potential answerers of questions in the social network.…”

“…Also, due to the anonymous global users, a question may not receive answers or the response delay may be long, and the provided answers may not be trustable (such as spam) or accurate [7]. To address these problems, more and more research efforts begin to study social-based Q&A systems [6,7,8,9,10,11,12]. Since social friends always share common-interests and they trust and like to help each other, the social-based Q&A systems rely on an asker's social friends to provide answers.…”