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Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems

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Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems ( online-social-networks-measurement-analysis-and-applications )

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174 conditionally classified as wanted. In this case, Ostra would need to operate only among users who are not on each other’s whitelists. 8.3.3 Parameter settings Ostra limits the amount of pending communication that a user can have, where a pending item of communication is one that was generated by the user but not yet classified by the receiver. In Section 8.4, we show that Ostra’s design parameters (L, U, and d) can be chosen such that most legitimate users are not affected by the rate limit, while the amount of unwanted communication is still kept very low. The L parameter controls the number of unclassified items of communication a user can have at any one time. A large L allows many outstanding messages but also admits the possibility that a considerable amount of this outstanding communication would be unwanted. In contrast, an L close to 0 ensures that very little unwanted communication is received, at the cost of potentially rate-limiting legitimate senders. The d parameter represents the rate at which users who have sent unwanted commu- nication in the past are “forgiven”. Setting d too high allows additional unwanted communication, whereas setting it too low may unduly punish senders who have in- advertently sent unwanted communication in the past. In the Section 8.4, we show that the conservative settings of L=–3 and d=10% per day provide a good trade-off in practice.

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