Knowledge sharing in virtual communities: a social exchange theory perspective

Purpose: The author tried to identify the knowledge sharing behaviors on the internet, using structural equation modeling methods, proposing a model based on social exchange theory in which share willingness, trust, reciprocity, altruism tended to have impact on people’s knowledge sharing behaviors in virtual communities. Design/methodology/approach: We presented an empirical research which integrated social exchange theory and structural equation modeling methods to analyze several important factors influencing members’ knowledge sharing behaviors in virtual communities. Findings: We analyzed the knowledge sharing behaviors in virtual communities. We found that members’ altruism can not predict knowledge sharing behaviors. We also found that members’ sharing willingness is the most important factor on virtual community knowledge sharing behaviors compared with trust, reciprocity and altruism. Originality/value: From the perspective of social exchange theory, we did empirical test and verified the proposed research model by using structural equation modeling methods. Our finding can help recognize people’s incentive about knowledge sharing.Peer Reviewe

Knowledge sharing in virtual communities: a social exchange theory perspective

Purpose: The author tried to identify the knowledge sharing behaviors on the internet, using structural equation modeling methods, proposing a model based on social exchange theory in which share willingness, trust, reciprocity, altruism tended to have impact on people’s knowledge sharing behaviors in virtual communities. Design/methodology/approach: We presented an empirical research which integrated social exchange theory and structural equation modeling methods to analyze several important factors influencing members’ knowledge sharing behaviors in virtual communities. Findings: We analyzed the knowledge sharing behaviors in virtual communities. We found that members’ altruism can not predict knowledge sharing behaviors. We also found that members’ sharing willingness is the most important factor on virtual community knowledge sharing behaviors compared with trust, reciprocity and altruism. Originality/value: From the perspective of social exchange theory, we did empirical test and verified the proposed research model by using structural equation modeling methods. Our finding can help recognize people’s incentive about knowledge sharing.Peer Reviewe

Knowledge sharing in virtual communities: a social exchange theory perspective

Purpose: The author tried to identify the knowledge sharing behaviors on the internet, using structural equation modeling methods, proposing a model based on social exchange theory in which share willingness, trust, reciprocity, altruism tended to have impact on people’s knowledge sharing behaviors in virtual communities. Design/methodology/approach: We presented an empirical research which integrated social exchange theory and structural equation modeling methods to analyze several important factors influencing members’ knowledge sharing behaviors in virtual communities. Findings: We analyzed the knowledge sharing behaviors in virtual communities. We found that members’ altruism can not predict knowledge sharing behaviors. We also found that members’ sharing willingness is the most important factor on virtual community knowledge sharing behaviors compared with trust, reciprocity and altruism. Originality/value: From the perspective of social exchange theory, we did empirical test and verified the proposed research model by using structural equation modeling methods. Our finding can help recognize people’s incentive about knowledge sharing.Peer Reviewe

A scalable location service for geographic ad hoc routing

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2001."January 2001."Includes bibliographical references (p. 55-57).GLS is a new distributed location service which tracks mobile node locations. GLS combined with geographic forwarding allows the construction of ad hoc mobile networks that scale to a larger number of nodes than possible with previous work. GLS is decentralized and runs on the mobile nodes themselves, requiring no fixed infrastructure. Each mobile node periodically updates a small set of other nodes (its location servers) with its current location. A node sends its position updates to its location servers without knowing their actual identities, assisted by a predefined ordering of node identifiers and a predefined geographic hierarchy. Queries for a mobile node's location also use the predefined identifier ordering and spatial hierarchy to find a location server for that node. Experiments using the ns simulator for up to 600 mobile nodes show that the storage and bandwidth requirements of GLS grow slowly with the size of the network. Furthermore, GLS tolerates node failures well: each failure has only a limited effect and query performance degrades gracefully as nodes fail and restart. The query performance of GLS is also relatively insensitive to node speeds. Simple geographic forwarding combined with GLS compares favorably with Dynamic Source Routing (DSR): in larger networks (over 200 nodes) our approach delivers more packets, but consumes fewer network resources.by Jinyang Li.S.M

Detection of Groups with Biased Representation in Ranking

Real-life tools for decision-making in many critical domains are based on ranking results. With the increasing awareness of algorithmic fairness, recent works have presented measures for fairness in ranking. Many of those definitions consider the representation of different ``protected groups'', in the top-$k$ ranked items, for any reasonable $k$. Given the protected groups, confirming algorithmic fairness is a simple task. However, the groups' definitions may be unknown in advance. In this paper, we study the problem of detecting groups with biased representation in the top-$k$ ranked items, eliminating the need to pre-define protected groups. The number of such groups possible can be exponential, making the problem hard. We propose efficient search algorithms for two different fairness measures: global representation bounds, and proportional representation. Then we propose a method to explain the bias in the representations of groups utilizing the notion of Shapley values. We conclude with an experimental study, showing the scalability of our approach and demonstrating the usefulness of the proposed algorithms

Spatially Fourier-encoded photoacoustic microscopy using a digital micromirror device

We have developed spatially Fourier-encoded photoacoustic (PA) microscopy using a digital micromirror device. The spatial intensity distribution of laser pulses is Fourier-encoded, and a series of such encoded PA measurements allows one to decode the spatial distribution of optical absorption. The throughput and Fellgett advantages were demonstrated by imaging a chromium target. By using 63 spatial elements, the signal-to-noise ratio in the recovered PA signal was enhanced by ∼4×. The system was used to image two biological targets, a monolayer of red blood cells and melanoma cells