In 2006, I submitted an MSc dissertation based on a research programme that I had independently funded through my own company. In 2026, twenty years later, I have decided to publish that dissertation in its original form.

It has not been revised, rewritten or retrospectively updated.

The document is published as a historical research artefact, preserving the observations, methods, analysis and conclusions that emerged from research conducted between 2004 and 2006.

At the time, I was not approaching the subject as a typical postgraduate student. I was already in my late thirties and had accumulated substantial commercial experience across technology, business systems and digital interaction. The primary research programme supporting the dissertation was funded independently through my company because I wanted the freedom to investigate questions that interested me without being constrained by externally defined commercial or academic objectives.

The research focused on digital consumer interaction, online shopping behaviour, human-computer interaction, interaction mapping and decision-making processes within internet environments. While many studies at the time sought to simplify behaviour into measurable variables, my interest was directed towards the areas where behaviour became inconsistent, contradictory or difficult to explain.

One of the central methodological decisions was to preserve contradictions and outliers rather than remove them.

Traditional research approaches often treat anomalous data as noise. My concern was that in many situations the anomaly is precisely where the interesting information exists. When people’s observed behaviour diverges from what they report, when individuals follow unexpected paths, or when decisions appear inconsistent with rational models, those deviations may reveal aspects of human interaction that would otherwise remain invisible.

This perspective attracted an interesting recent observation from Nils Roeder, who commented:

Keeping contradictions and outliers instead of cleaning them is point on! The odd cases often show where actual behaviour departs from what people report.

That comment resonated strongly with me because it captures one of the core motivations behind the research.

My response was simple:

I have made hundreds of thousands of pounds with this way of working over the last 20 years. I always find things that others cannot because their processes eliminate the trail to find them.

That statement is not about academic methodology alone. It reflects a practical lesson that has repeatedly proven valuable in commercial environments. Whether analysing customer behaviour, designing systems, investigating organisational problems or developing new products, the most valuable insights often exist in the data that conventional processes discard.

The dissertation explored this through a dialectic enquiry methodology that deliberately preserved tension, contradiction and competing interpretations. Rather than forcing consistency, the research examined how contradictory evidence could contribute to understanding human activity within digital environments.

This led to the exploration of concepts including:

• Drivers
• Trajectories
• Choice gateways
• Biographical templates
• Temporal narratives
• Interaction mapping
• Interaction language

These concepts were developed as mechanisms for examining intention, behaviour and meaning within digital systems.

The concept of interaction language emerged from an unusual line of enquiry. Part of the methodological approach was influenced by the techniques used in the discovery and interpretation of lost languages, where meaning must be inferred from fragments, patterns, context, repetition and relationships rather than from direct explanation. In much the same way, digital interactions can be viewed as traces of underlying intention and meaning. Rather than treating clicks, navigation paths and behavioural events as isolated data points, the research explored whether they could be interpreted as components of a broader interaction language through which individuals expressed intent, purpose, uncertainty, preference and decision-making within digital environments.

This approach helped shape the development of interaction mapping and contributed to a wider examination of how meaning is created, communicated and interpreted between humans and technological systems.

The research also examined the influence of Socratic and Dialectic traditions on knowledge acquisition and interpretation. A proposition running throughout the dissertation was that the logical methods used in research directly influence what becomes visible, measurable and explainable. In other words, methodology does not simply reveal knowledge; it actively shapes the knowledge that can be discovered.

Looking back from 2026, I find it particularly interesting that many of the questions explored by the dissertation have become even more relevant. Today, AI systems, behavioural analytics platforms and recommendation engines routinely attempt to infer human intent from observed behaviour. In many respects, they face the same challenge that linguists face when interpreting an unfamiliar language: meaning cannot be observed directly and must be inferred from patterns, context and interaction. The research was, in part, an early attempt to examine that problem within digital environments.

This publication should not be read as a contemporary statement of current research. It should be read as a preserved record of an intellectual journey undertaken between 2004 and 2006.

The dissertation contains anonymised research data extracts reproduced from the original submission. Participant identities remain protected through coded identifiers. The work is published exactly as submitted and reflects the methods, observations, interpretations and conclusions reached at that time.

I am grateful to Dr Susan Turner for her guidance, support and encouragement throughout the project, and to Tom McEwan, Head of Course, for his support and contribution during the research and completion of the dissertation.

The publication forms part of a much longer body of work exploring interaction, meaning, identity and digital systems. While many of the terms and concepts have evolved over the intervening twenty years, the questions that inspired the research remain remarkably similar:

• How do people create meaning?
• How do they make decisions?
• How do they interact with systems?

And what do we lose when we simplify human behaviour to fit the limits of our analytical models?

Perhaps the most important lesson I took from the work is the same one that continues to guide my thinking today:

Sometimes the answer is not hidden in the signal.

Sometimes it is hidden in what everyone else has decided is noise.

Read or Download the Full Paper Here: https://doi.org/10.6084/m9.figshare.33941128.v1