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trust-based network. 8.4.2 Experimental traffic workload We were unable to obtain a communication trace of the same scale as the social net- work we use. Therefore, we had to make some assumptions about the likely commu- nication pattern within the social network. We expect that users communicate with nearby users much more often than they communicate with users who are far away in the social network. To validate this hypothesis, we collected an email trace from the Max Planck Institutes for Informations and Software Systems, consisting of two aca- demic research institutes with approximately 200 researchers. Our anonymized email trace contains all messages sent and received by the mail servers for 100 days, and the anonymized addresses in the trace are flagged as internal or external addresses. Similar to previous studies [28,143], we extracted a social network from the email data by examining the messages sent between internal users. Specifically, we created a symmetric link between users who sent at least three emails to each other. We filtered out accounts that were not owned by actual users (e.g., helpdesk tickets and mailing lists), resulting in a large strongly connected component containing 150 users and covering 13,978 emails. We then examined the social network distance between sender and receiver for all messages sent between these 150 users. Figure 8.7 compares the resulting distance distribution with one that would result had the senders selected random destinations. 177PDF Image | Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems
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