Social network analysis in the context of "Social network"

In social network analysis and mathematical sociology, interpersonal ties are defined as information-carrying connections between people. Interpersonal ties, generally, come in three varieties: strong, weak or absent. Weak social ties, it is argued, are responsible for the majority of the embeddedness and structure of social networks in society as well as the transmission of information through these networks. Specifically, more novel information flows to individuals through weak rather than strong ties. Because our close friends tend to move in the same circles that we do, the information they receive overlaps considerably with what we already know. Acquaintances, by contrast, know people that we do not, and thus receive more novel information.

Included in the definition of absent ties, according to the American sociologist Mark Granovetter, are those relationships (or ties) without substantial significance, such as "nodding" relationships between people living on the same street, or the "tie", for example, to a frequent vendor one would buy from. Such relations with familiar strangers have also been called invisible ties since they are hardly observable, and are often overlooked as a relevant type of ties. They nevertheless support people's sense of familiarity and belonging. Furthermore, the fact that two people may know each other by name does not necessarily qualify the existence of a weak tie. If their interaction is negligible the tie may be absent or invisible. The "strength" of an interpersonal tie is a linear combination of the amount of time, the emotional intensity, the intimacy (or mutual confiding), and the reciprocal services which characterize each tie.

Traffic analysis is the process of intercepting and examining messages in order to deduce information from patterns in communication. It can be performed even when the messages are encrypted. In general, the greater the number of messages observed, the greater information be inferred. Traffic analysis can be performed in the context of military intelligence, counter-intelligence, or pattern-of-life analysis, and is also a concern in computer security.

Traffic analysis tasks may be supported by dedicated computer software programs. Advanced traffic analysis techniques which may include various forms of social network analysis.

Social contagion involves behaviour, emotions, or conditions spreading spontaneously through a group or network. The phenomenon has been discussed by social scientists since the late 19th century, although much work on the subject was based on unclear or even contradictory conceptions of what social contagion is, so exact definitions vary. Some scholars include the unplanned spread of ideas through a population as social contagion, though others prefer to class that as memetics. Generally social contagion is understood to be separate from the collective behaviour which results from a direct attempt to exert social influence.

Two broad divisions of social contagion are behavioural contagion and emotional contagion. The study of social contagion has intensified in the 21st century. Much recent work involves academics from social psychology, sociology, and network science investigating online social networks. Studies in the 20th century typically focused on negative effects such as violent mob behaviour, whereas those of the 21st century, while sometimes looking at harmful effects, have often focused on relatively neutral or positive effects like the tendency for people to take action on climate change once a sufficient number of their neighbours do.

Dynamic network analysis (DNA) is an emergent scientific field that brings together traditional social network analysis (SNA), link analysis (LA), social simulation and multi-agent systems (MAS) within network science and network theory. Dynamic networks are a function of time (modeled as a subset of the real numbers) to a set of graphs; for each time point there is a graph. This is akin to the definition of dynamical systems, in which the function is from time to an ambient space, where instead of ambient space time is translated to relationships between pairs of vertices.

Heterophily (meaning "love of the different") is the tendency of individuals to collect in diverse groups; it is the opposite of homophily. This phenomenon can be seen in relationships between individuals. As a result, it can be analyzed in the workplace to create a more efficient and innovative workplace. It has also become an area of social network analysis.

Graph drawing is an area of mathematics and computer science combining methods from geometric graph theory and information visualization to derive two-dimensional (or, sometimes, three-dimensional) depictions of graphs arising from applications such as social network analysis, cartography, linguistics, and bioinformatics.

A drawing of a graph or network diagram is a pictorial representation of the vertices and edges of a graph. This drawing should not be confused with the graph itself: very different layouts can correspond to the same graph. In the abstract, all that matters is which pairs of vertices are connected by edges. In the concrete, however, the arrangement of these vertices and edges within a drawing affects its understandability, usability, fabrication cost, and aesthetics. The problem gets worse if the graph changes over time by adding and deleting edges (dynamic graph drawing) and the goal is to preserve the user's mental map.