Skopenow Link Analysis Chart

By Stephen Adams, Product Marketing Manager, Skopenow

Connections are the lifeblood of the internet, with people and businesses interacting and leaving digital footprints on social media platforms, online marketplaces, websites and forums at all hours of the day. For OSINT For professionals, these myriad interactions are not just noise, they are critical data points that can reveal hidden networks and relationships.

Through link analysis, OSINT professionals can obtain valuable information based on online activity and public records of individuals and organizations, and use that information to generate more comprehensive intelligence. In the past, link analysis involved manually combing through large volumes of data and spreadsheets to build association matrices, and finally shaping them into rudimentary link analysis graphs. The researchers took on this hard work to better understand isolated data sets and to identify patterns, outliers, and other links. However, with modern automated OSINT solutions, what used to take researchers hours or even days can now be accomplished in minutes.

What is link analysis?

Link analysis is a visual data technique used to assess relationships and connections between entities, including people, businesses, objects (such as property and vehicles), and activities. The ultimate goal of link analysis is to produce an insightful visual snapshot encompassing a complete set of raw data, using icons and links to highlight certain overlapping data points. The visual is crucial because it makes it easy to “see” relationships that would otherwise be missed by looking at the raw data.

Given the importance of link analysis as an OSINT technique, it is vital to understand what a link analysis graph is and how graphs are assembled. A link analysis graph is made up of interconnected nodes, which are points that represent an object, such as a person, place, or activity. Connecting the nodes are lines, or “links,” that represent the connections between the nodes, such as a workplace, business property, kinship, and other relationships. The series of nodes and links collectively represent a network.

By connecting people and companies to shared data points, such as addresses, phone numbers, social media accounts, and vehicles, investigators can understand how various entities share commonalities to quickly and efficiently identify fraud or other illegal activity.

Why use link analysis?

The human brain processes visual information much faster than written information, which is why link analysis is so powerful. When data is presented in robust link analysis graphs, researchers and other stakeholders can more quickly understand patterns and narratives, avoiding the time and effort required to review extensive reports or thousands of rows of data.

One example where link analysis is especially valuable is in cases of auto insurance fraud and organized crime. Using modern tools, investigators can trace links between family groups, auto body shops, towing companies, car rental companies, law firms and more. The ability to connect these dots allows investigators to efficiently identify fraudulent activities and schemes. This information can then be presented to law enforcement or the district attorney’s office as a link analysis graph to highlight key themes contained in the supporting evidence.

Link analysis for OSINT investigations and fraud detection

Criminals leave digital activity trails when they conduct illegal activities online. These traces are often fragmented and seem disconnected at first. To link criminals to illicit activities, investigators must connect all of these traces to get a clear picture. The application of link analysis to a matrix of data sets allows the detection of new connections and generates a visualization of the relationships between the parties involved.

Again using the example of insurance fraud investigations, insurers seek to uncover false or exaggerated claims through link analysis and often want to determine how many degrees of separation exist between the claimant and known or suspected fraudsters. The organization can then improve its processes to determine which claims it should pay and which require further investigation, based on its risk appetite. Reducing fraud with this approach can save a company a lot of time and money.

Whether fighting fraud, investigating criminal acts, or prosecuting attackers, link analysis provides investigators with evidence about key relationships between different nodes in a large network, enabling investigators and their organizations to take informed action. and effective.

Scale link analysis and what success looks like

Organizations that adopt modern link analytics solutions are poised to detect more fraudulent and illegal activity while disrupting more criminals than ever thought possible. Identifying the right connections, motivations, and opportunities empowers researchers to build strong cases based on factual evidence and strong supporting narratives.

To effectively leverage link analytics for many complex investigations, organizations must employ an automated link analytics solution. Automation allows research teams to analyze structured and unstructured data at the click of a button and identify important connections hidden within huge data sets. Understanding these connections enables investigators to turn disparate data points into actionable intelligence, leading to superior decision making and case outcomes.

Solutions like Skpenow’s link analysis and pre check Research teams use them to ingest large amounts of data, discover connections between entities contained in that data, and summarize and display associations in a simple and straightforward format. Skopenow offers can support thousands of parties at a time. Even better, while countless organizations struggle to justify hiring in-house researchers or performing link analysis due to the technical skills and resources required, Skopenow removes those hurdles by automatically generating link analysis graphs without the need for special training, certifications, or IT support.

Link Analysis and Pre-Check are available to start modernizing your investigations today. Request a demo and free trial today at to see firsthand how Skopenow can help your organization unlock the power of open source intelligence.

About the Author

Steve is a security and crime intelligence specialist working with a focus on Internet investigations, helping decision makers make informed, data-driven decisions to reduce crime. As a product marketing manager at Skopenow, an emerging leader in open source intelligence (OSINT) solutions, she drives messaging on key features and benefits of the Skopenow platform, helps bring technology products to market, and demonstrates techniques for research in Internet.

With a background in UK law enforcement, Steve has extensive experience providing security and criminal intelligence training and education and has supported hundreds of criminal investigations to successfully reduce crime rates and prosecute offenders. Leading OSINT training webinars and speaking at conferences in the US and UK, he frequently discusses how to unlock the power of OSINT for live audiences, showing how it can be harnessed to streamline Internet investigations.

About Skopenow

Skopenow is a leading provider of comprehensive threat intelligence and OSINT solutions. The company’s research products are used by more than 1,000 clients, including 20% ​​of the Fortune 500, as well as numerous government and law enforcement agencies. Skopenow enables organizations to collect and analyze open source information more effectively and efficiently, identify trends and patterns in data, and detect emerging threats and fraud. Founded in 2016 and headquartered in New York City, Skopenow is a high-growth, venture-backed technology company.

Skopenow works with insurance companies, law firms, global security teams, government agencies, media companies, licensed private investigators, investigators, law enforcement agencies, and more. For more information please visit

Source: Skopenow

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