Tips: 13.05.22

How link analysis done right can be the key to solving cases faster

"A butterfly can flutter its wings over a flower in China and cause a hurricane in the Caribbean," Robert Redford said in Havana.

That line may be one of the clearest encapsulations of what you do as an analyst: recognize the relationship between seemingly unrelated things to understand the connections between people, objects, actions and events. It’s why investigations value link analysis so much: the better you are at analyzing connections, the faster you can crack a case.

Done right, link analysis can simplify the entire intelligence cycle, from data collection to drawing conclusions.But link analysis isn’t always easy to do in practice. Challenges with technology, usability and clarity can make your job harder and disrupt your workflow.

That’s why we compiled the major issues getting in the way of effective link analysis, from our customers and personal experiences — plus our solutions to overcome them.

Let’s dive in.

What does successful link analysis look like?

Say you are studying an organization. Every person in that organization is an individual, represented as a node. Each relationship, or link, gives more context to your understanding of that organization and your investigation. Layer those nodes and links with metadata like phone records or social media interactions, and you can make better-informed decisions and conclusions.

Unfortunately, this simple idea can be very complicated in practice. And that’s the biggest problem with most link analysis graphing solutions: too many loose connections, non-starters and dead-ends getting in the way of the clear, traceable truth.

Here’s how they get in the way of your goals.

Common issues with link analysis

Technical issues

Link analysis graphs may be too dense for readable automated layouts
Nodes, especially when sized differently, can be hard to manage
Algorithms may pile nodes on top of each other
Big graphs may cause lag, reducing performance and user experience

Human-machine interaction issues

Too many nodes and links can make it virtually impossible to draw meaningful insight. People can only store roughly seven things in their short-term memory at a time. So how can one interpret thousands of nodes on a noisy graph?
A mass of visualized data can make it hard to locate the most relevant nodes or understand the meaning behind a node’s placement
Nodes may fail to show all the required information
Overuse of colors can confuse or obscure information

Intelligence value issues

Strength and/or type-of connection between nodes may lack clarity
Time isn’t properly integrated or symbolized
Parameters and filters may be poorly executed for groups
A lack of knowledge or methodology may get in the way of reading the link analysis graph and/or drawing the right insights

So, how can we solve these problems?

Introducing Falkor: analyzing connections made easy

Analysts collect data from a range of sources. Falkor makes it easy to collect, combine and analyze data all in one place.
Duplicate data and unnecessary nodes clog relevant data. Falkor’s AI helps analysts graph only the most relevant and valuable data for link analysis.
Avoid overwhelming graphs with Falkor. Organize nodes into tidy, nestable clusters based on properties or placement.
Create your ideal workflow. Add and edit your investigation from an empty canvas with Falkor’s opt-in ability.
Dense, stacked nodes can obscure meaningful information. Zoom in and out to hone in on relevant data clearly and easily.
Hide excess information and data noise. Neat user experience and minimized side viewing options let you see your link analysis and nothing else.
Solving cases is about targeting the most relevant information. Filter data by labels like name, location and other properties.
It’s not just that entities are related, it’s how they’re related. Easily explore relationships with clearly-defined links.
By using the same colors to symbolize features and relationships throughout different aspects of Falkor, analyzing connections becomes effortless.
Nodes are logically located in the same place on an X & Y-axis. Unless the analyst selects a different layout or changes the link analysis’ graph’s properties.
Instead of wading through dense layers of nodes, our scatter option allows you to spread nodes in your current view to eliminate touching and overlapping.
Drag, drop and select multiple nodes simultaneously. So you can extract several insights at once without losing sight of your ultimate goal.
Save and share light-bulb moments with notes and snapshots, helping you remember the insights that led to your conclusion.
Click nodes for pop-ups containing key properties and data, making information accessible without crowding your link analysis graph.
Falkor is developed by analysts, for analysts. And with visualizations that simplify and support your process, including web charts, timelines tables and maps.
Transform your data and discoveries into ready-to-publish reports in an instant.

Revolutionizing the intelligence cycle

Done right, link analysis can simplify the entire intelligence cycle, from data collection to drawing conclusions. That’s why we developed Falkor, the first platform where analysts can unite and manage data from multiple sources to drive the discovery, analysis and reporting in any investigation.