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65 a different 11.3% subset gathered in the same way. In other words, are the properties of our sample representative of other samples of similar size? The second concern is whether the properties of our sample are representative of the properties of the network as a whole. To explore the first of these concerns, we conducted five separate, small crawls of Orkut starting from random locations. Our random starting locations were cho- sen using Maximum-Degree random sampling [11] configured with a path length of 100,000 hops. Each of the five crawls was configured to cover 80,000 nodes in the same manner as our single, large crawl. We then compared the properties of the resulting samples. We found that the properties of the five smaller crawls were similar, even though these crawls covered only 0.29% of the network each. For example, we found that the clustering coefficient of these crawls had an average of 0.284 with a standard deviation of 0.040. Similarly, we found that the scale-free metric had an average of 0.550 with a standard deviation of 0.083 (both of these metrics are discussed in more detail in the following section). Thus, we believe that the properties of our 11.3% sample of the network are likely to be similar to other crawls of similar size that are done in the same manner. However, we caution the reader to be mindful of the second concern when extrap- olating the results from our crawl to the entire Orkut network. Partial BFS crawls are known to over-sample high-degree nodes, and under-sample low-degree nodes [85].PDF Image | Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems
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