Networks are sets of nodes and ties connecting some of the nodes. Network analysis is a multidisciplinary venture to understanding various types of phenomena, and it has a long history on its own. Beyond social networks (i.e. network analysis between people), it can be used to examine hyperlinks, transportation systems, qualitative data (text) and relationships between objects and actors (actor-network theory) - among many other things. This versatility is helped through different conceptualisations about what a network is: directed or undirected, weighted or unweighted and multi-layered or single-layered. Furthermore, networks may have attributes that further provide depth to the analysis tools.
Network analysis may be descriptive. There are several aspects that can be measured from the network: degree, average path length or the number of triadic closures. So, some of the measures focus on nodes and others describe the network as a whole. Furthermore, networks can be visualised for inspection. Many opportunities to vary the nodes, ties and layout exist.
Beyond traditional descriptive analysis, networks can also be analysed using computationally heavy approaches. For example, algorithms can be used to examine what kinds of communities or clusters emerge in the network. Randomness may be used to quantify how common or rare a phenomenon observed in the network is. Both of these computationally heavy approaches provide additional insights to networking that is not possible through descriptive analysis alone.
As illustrated in the chapter, many approaches, tools and concepts are available for networks. The challenge is to build strong research questions that take benefit from opportunities provided by the versatile network analysis paradigm. Therefore, network analysis provides many opportunities for both sociological and technological imagination.