Abstract: The present invention proposes that the value of a crowd network comes from network entropy and a very well engaged crowd has more value than a poorly engaged crowd. The engagement (and the resultant value generated from the engagement) of a crowd network can be measured in terms of the entropy of the network. The entropy is calculated as a function of the probability distribution of incoming and outgoing messages, which represents the entropy or uncertainty in the activity over the network. In this way, the activity occurring over a network in terms of message exchange is translated as a measure of the value of the network. An evolutionary algorithm is presented to optimize the entropy of a network by successively changing the network topology. Results indicate that the value of a crowd network very closely relate to its small world-ness, sparsity, and connectedness.

Abstract: The present invention proposes that the value of a crowd network comes from network entropy and a very well engaged crowd has more value than a poorly engaged crowd. The engagement (and the resultant value generated from the engagement) of a crowd network can be measured in terms of the entropy of the network. The entropy is calculated as a function of the probability distribution of incoming and outgoing messages, which represents the entropy or uncertainty in the activity over the network. In this way, the activity occurring over a network in terms of message exchange is translated as a measure of the value of the network. An evolutionary algorithm is presented to optimize the entropy of a network by successively changing the network topology. Results indicate that the value of a crowd network very closely relate to its small world-ness, sparsity, and connectedness.

Abstract: As social networks become more powerful and sophisticated, each member of a social network may belong to different communities. The computing reputation for users in a single community is not adequate anymore. As a result, a method of calculating global reputation for each member is desirable. Various considerations are described to address challenges related to global reputation for a user who participates in activities among multiple communities. Considerations on accessibility of a community, quality vs. quantity of submissions, posting ideas vs. comments, weighting of each community, and volatility of the reputation value are discussed in the present invention. Finally, a formula for calculating a global reputation value of the user is proposed by combining all the considerations. A system that implements the global reputation computation is described.

Abstract: A rating system provides a mechanism whereby users can submit objects to be rated (ROs), and whereby users can submit ratings (ARs) regarding the ROs of other users. In a first novel aspect, each AR is multiplied by a weighting factor to determine a corresponding effective rating (ER). The weighting factor that is used to determine an ER from an AR is a function of the reputation RPT of the user who submitted the AR. In a second novel aspect, the weighting factor is also a function of a crowd voting probability value PT. In a third novel aspect, the weighting factor is also a function of the freshness RF of the AR. In a fourth novel aspect, a decay value D is employed in determining a user's reputation. ERs are used to determine a ranking of ROs. User reputation is used to determine a ranking of users.