What Is Link Analysis?

Link analysis is a powerful analytical technique professionals use to understand the structure and relationship of units within a network. Given the ever-growing amount of data, it’s particularly critical to be able to leverage data from multiple sources and understand why and how it’s all connected. In turn, link analysis can speed up the rate of gaining valuable insights and improve scalability.

In this article, explore what link analysis is, why you might choose to use it, and the applications of link analysis you may see in different professional fields.

What is link analysis?

This data analysis technique evaluates the relationships or connections between nodes within a network. A node can represent virtually anything—individuals in a social network, interconnected web pages, genes in a biological network, etc. Link analysis calculates measures between the nodes, such as their closeness, betweenness, and degree, all of which are centrality measures. The focus of link analysis is to understand the structure and properties of the network through its links (or edges), which connect these nodes. 

Link analysis purpose

Link analysis serves various analytical applications that depend on understanding relationships between entities. Examining the connections or links within a data set can offer insights into different domains, informed by attributes that characterize these links. The following are some uses for link analysis.

Read more: 10 Data Analysis Tools and When to Use Them

1. Find matches

Link analysis can identify connections based on multiple variables or attributes. For instance, analyzing telephone call detail records could reveal links between two telephone numbers. The algorithm determines the links’ characteristics through the frequency, duration, and timing of these calls.

2. Find anomalies

Link analysis aids in anomaly detection by evaluating links between entities and considering the weight or characteristics of these connections. Identifying abnormal network activity, for instance, can help expose illegal activities or security threats. It can also flag unusual behaviors in other types of networks, like financial transactions.

3. Find patterns

Link analysis is instrumental in process optimization and decision-making. For example, in public health studies, you might look for socioeconomic characteristics and health outcomes patterns. Doing so may help you understand how different community and population factors could relate to risk factors over time.

4. Assess influence

In social networking environments, link analysis can evaluate an individual's viral influence. Even if one participant does not account for a significant number of product purchases, their recommendations could carry substantial weight within their “sphere of influence,” affecting the behavior of many others in their network.

Why choose link analysis? Pros and cons

Link analysis offers several advantages and disadvantages that can either facilitate or limit its utility in various applications. When working with link analysis, you might observe both the pros and cons of this method.

Advantages

Depending on your application, your advantages will vary. However, many professionals experience the following benefits when using link analysis:

• Objective insight: Link analysis can objectively capture exploratory data, such as tracking where and how professionals complete tasks.

• Ease of use: The technique doesn’t require substantial training in data collection or analysis.

• Time efficiency: Depending on the scope of the project, link analysis often doesn’t consume much time, making it a quick method for gathering insights.

• Quick pattern recognition: Link analysis aids in rapidly identifying trends and outliers. You can apply this across many field applications.

• Scalable: Many applications of link analysis scale to fit the level of complexity you’re dealing with.

Disadvantages

As with any method, you are also likely to find disadvantages. Some disadvantages you might uncover with this method include:

• Limited scope in certain domains: In some cases, link analysis cannot capture all of the relevant information. For example, in work tracking, link analysis only examines the physical aspects of work, missing out on capturing the cognitive processes involved in task completion.

• Risk of overinterpretation: It could be easy to overinterpret the identified relationships, especially those with unequal distributions. You need to exercise caution to avoid making overarching claims based on the data. 

• Domain-specific knowledge required: To reduce certain risks of link analysis, you need a comprehensive understanding of the domain and the data.

What industries use link analysis?

Link analysis is a versatile analytical tool that finds applications across various sectors, each with its unique demands and objectives. Some industries where link analysis has proven to be invaluable include:

Social media networking

In social media, professionals employ link analysis to map out how users connect to one another, who influences whom, and what communities exist within the more extensive network. By examining these links, companies can better understand user behavior, influence, and the diffusion of information or trends.

Aerospace and communication

Organizations like NASA use link analysis to optimize legacy communication networks and telemetry assets. Understanding the intricate connections between various nodes in these networks helps in better allocation of resources and risk management.

Marketing

In marketing, link analysis applies to studying consumer behavior, such as how customers with a particular purchase history are likely to behave. It helps marketers optimize advertising campaigns and effectively target specific customer segments.

Transactions

Link analysis can detect fraud or other irregularities in financial and transactional settings. By studying the links between different transactions or accounts, you can spot anomalies that could indicate fraudulent activity more easily.

How to begin learning link analysis

Link analysis doesn’t necessarily require extensive background knowledge but involves a keen interest in understanding relationships within data sets. Consider these approaches to begin learning how to apply link analysis:

• Start basic: Familiarize yourself with basic concepts of networks, nodes, and edges. Identify where you have knowledge gaps and focus on building your foundation.

• Take time to browse available resources. Read introductory articles or watch explainer videos on graph visualization and link analysis. Link theory is heavily rooted in network analysis and graph theory, so choosing resources in this topic space might benefit you.

• Take online courses: Enroll in beginner courses that offer a structured approach to link analysis.

By starting small and gradually building your skill set, you’ll be well-equipped to leverage link analysis in various professional contexts.

Next steps

Link analysis is an aspect of graph theory that helps data analysts, social media specialists, fraud detectors, and scientists visualize connections in their data to discover anomalies and patterns. You can continue learning about link analysis and related topics by taking courses from top universities on Coursera. You may begin with Data Analysis and Reporting in SAS Visual Analytics by SAS to learn fundamental data analysis, data visualization, and business intelligence skills. Or try the Social Network Analysis course from the University of California Davis to understand the language of networks through social network analysis case studies. The course is a part of the Computational Social Science Specialization, also found on Coursera.