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Social network (sociolinguistics)

Social network (sociolinguistics) is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Social network (sociolinguistics) rather than just read about it. In short: In the field of sociolinguistics, social network describes the structure of a particular speech community. Social networks are composed of a "web of ties" (Lesley Milroy) between individuals, and the structure of a network will vary depending on the types of connections it is composed of.

Social network (sociolinguistics) — main illustration
Social network (sociolinguistics) — illustration

Key takeaways

  • Social network (sociolinguistics) belongs to computer science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Social network (sociolinguistics) to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Social network (sociolinguistics) from memory before moving on to harder problems.

Reference excerpt

In the field of sociolinguistics, social network describes the structure of a particular speech community. Social networks are composed of a "web of ties" (Lesley Milroy) between individuals, and the structure of a network will vary depending on the types of connections it is composed of. Social network theory (as used by sociolinguists) posits that social networks, and the interactions between members within the networks, are a driving force behind language change.

Structure

Participants The key participant in a social network is the anchor, or center individual. From this anchor, ties of varying strengths radiate outwards to other people with whom the anchor is directly linked. These people are represented by points. Participants in a network, regardless of their position, can also be referred to as actors or members.

Relationships There are multiple ways to describe the structure of a social network. Among them are density, member closeness centrality, multiplexity, and orders. These metrics measure the different ways of connecting within of a network, and when used together they provide a complete picture of the structure of a particular network. A social network is defined as either "loose" or "tight" depending on how connected its members are with each other, as measured by factors like density and multiplexity. This measure of tightness is essential to the study of socially motivated language change because the tightness of a social network correlates with lack of innovation in the population's speech habits. Conversely, a loose network is more likely to innovate linguistically.

Density The density of a given social network is found by dividing the number of all existing links between the actors by the number of potential links within the same set of actors. The higher the resulting number, the denser a network is. Dense networks are most likely to be found in small, stable communities with few external contacts and a high degree of social cohesion. Loose social networks, by contrast, are more liable to develop in larger, unstable communities that have many external contacts and exhibit a relative lack of social cohesion.

Member closeness centrality Member closeness centrality is the measurement of how close an individual actor is to all the other actors in the community. An actor with high closeness centrality is a central member, and thus has frequent interaction with other members of the network. A central member of a network tends to be under pressure to maintain the norms of that network, while a peripheral member of the network (one with a low closeness centrality score) does not face such pressure. Therefore, central members of a given network are typically not the first members to adopt a linguistic innovation because they are socially motivated to speak according to pre-existing norms within the network.

Multiplexity Multiplexity is the number of separate social connections between any two actors. It has been defined as the "interaction of exchanges within and across relationships". A single tie between individuals, such as a shared workplace, is a uniplex relationship. A tie between individuals is multiplex when those individuals interact in multiple social contexts. For instance, A is B's boss, and they have no relationship outside of work, so their relationship is uniplex. However, C is both B's coworker and neighbor, so the relationship between B and C is multiplex, since they interact with each other in a variety of social roles.

Orders Orders are a way of defining the place of a speaker within a social network. Actors are classified into three different zones depending on the strength of their connection to a certain actor. The closer an individual's connection to the central member is, the more powerful an individual will be within their network. Social network theories of language change look for correlation between a speaker's order and their use of prestigious or non-prestigious linguistic variants.

First order zone A first order zone is composed of all individuals that are directly linked to any given individual. The first order zone can also be referred to as the "interpersonal environment" or "neighborhood". A first order member of a network is an actor who has a large number of direct connections to the center of the network.

Second order zone A second order zone is a grouping of any individuals who are connected to at least one actor within the first order zone. However, actors in the second order zone are not directly connected to the central member of the network. A second order member has a loose or indirect connection to the network, and may only be connected to a certain network member.

Third order zone A third order zone is made up of newly observed individuals not directly connected to the first order zone. Third order members may be connected to actors in the second order zone, but not the first. They are peripheral members of the network, and are often the actors with the lowest member closeness centrality, since they may not have frequent contact with other members of the network.

Language change

Sociolinguistic research

… excerpt ends here. Continue reading the full article.

Illustrations

Social network (sociolinguistics): Visualization of snowball sampling technique showing two sampling zones. The first-order zone contains 7 individuals (black nodes). The second-order zone contains individuals that have direct contact to individuals in the first-order zone. The circles indicate the boundaries of the zones.
Visualization of snowball sampling technique showing two sampling zones. The first-order zone contains 7 individuals (black nodes). The second-order zone contains individuals that have direct contact to individuals in the first-order zone. The circles indicate the boundaries of the zones.
Social network (sociolinguistics): Map of central Belfast
Map of central Belfast

Worked examples

Example 1 — a first encounter with Social network (sociolinguistics)

Start with the simplest possible case. Write down what Social network (sociolinguistics) claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Social network (sociolinguistics) before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Social network (sociolinguistics) ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Social network (sociolinguistics)

In research
Social network (sociolinguistics) appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Social network (sociolinguistics) in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Social network (sociolinguistics) is common in secondary-school and first-year university syllabi. It links to neighbouring topics Linguistics terminology, Sociolinguistics, so understanding it makes those chapters shorter.
In everyday life
Look for Social network (sociolinguistics) outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Social network (sociolinguistics) in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Social network (sociolinguistics) means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Social network (sociolinguistics) out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Social network (sociolinguistics) in simple terms?

In the field of sociolinguistics, social network describes the structure of a particular speech community. Social networks are composed of a "web of ties" (Lesley Milroy) between individuals, and the structure of a network will vary depending on the types of connections it is composed of.

Why does Social network (sociolinguistics) matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Social network (sociolinguistics)?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Social network (sociolinguistics).

Tags

  • Linguistics terminology
  • Sociolinguistics

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