The properties of online social networks are of great interests to the general public as well as IT professionals. Often the raw data are not available and the summaries released by the service providers are sketchy. Thus sampling is needed to reveal the hidden properties and structure of the underlying network. This thesis conducts comparative studies on various sampling methods, including Ran...

Due to the large scales and limitations in accessing most online social networks, it is hard or infeasible to directly access them in a reasonable amount of time for studying and analysis. Hence, network sampling has emerged as a suitable technique to study and analyze real networks. The main goal of sampling online social networks is constructing a small scale sampled network which preserves t...

Recently, there has been a great deal of research focusing on the development of sampling algorithms for networks with small-world and/or power-law structure. The peerto-peer research community (e.g., [7]) have used sampling to quickly explore and obtain a good representative sample of the network topology, as these networks are hard to explore completely and have significant amounts of churn i...

Virtually all empirical ecological interaction networks to some extent suffer from undersampling. However, how limitations imposed by sampling incompleteness affect our understanding of ecological networks is still poorly explored, which may hinder further advances in the field. Here, we use a plant-hummingbird network with unprecedented sampling effort (2716 h of focal observations) from the A...

Network motifs are small connected subnetworks within a larger network that occur in statistically significant quantities and may indicate functional regions of the network. Network motif software tools employ algorithms that compare a network to randomly generated networks in order to identify subnetworks that occur in frequencies higher than would be expected by random chance. The transcripti...