
Neogenerative Semiotics / Foundations
[Part 1/3]: The shape of meaning
From peak to blob: How meaning emerges and changes shape over time and in context
01
The shape of meaning
Understanding and designing the “shape” of meaning between sign, context and time, when meaning stops “obeying”.
For a long time, I thought of meaning as a fixed, precise point, almost defined and unambiguous. Over time, I learned otherwise: meaning is something very fluid. Sometimes it takes the shape of its container, but often it is hard to tame and keep where we want it.
Imagine saying the word “authentic”. Simple, right? But it depends on who says it, when, where and in what tone. In the mouth of a Calabrian cook, “authentic” means tradition, grandmother, good olive oil. For a TikTok influencer, it might mean: “I do not use filters, look how real I am.” In an advertising tagline, unless you are careful, it sounds like fluff: “authentic like the taste of the past”, which usually tastes of prefabricated marketing. This is where the Semantic Gaussian comes in. It seems a simple idea, perhaps it is. But once you understand that a word does not “mean” just one thing, that it is a field of possibilities concentrated around a shared core and fading towards peripheral readings, the game becomes truly interesting.
This is the working intuition behind the Gaussian distribution of meaning: a central peak, the prevailing interpretation, with lateral tails, the minority readings – nuanced, sometimes ironic or even ambiguous. Then there is time, hardly a trivial variable in some contexts, especially today when the pace of change keeps accelerating. We are talking about a Gaussian with a somewhat atypical shape, not quite symmetrical like the perfect curves. It also changes over time, deforming, adapting, bending under the weight of events and contexts. If you work in branding, invent a tagline or even write a post and ignore this, rest assured that Gaussian will eventually turn against you. Because one day your “authentic” means trust. The next, it means fake.
Do you know the problem? We often stop at the idea of a curve: a neat, symmetrical, textbook Gaussian. But our work does not live on a sheet of paper. It lives in reality, where there is always at least one more variable to consider. Or rather, three.
Essential glossary
- Gaussian distribution of meaning: a curve with a central peak and interpretative tails.
- Gaussian Semiotic Cloud: the multidimensional distribution that evolves over time.
- Precipitation: the area where readings concentrate in a given context.
- Blur/Parallax/ThroughView Semiosis: techniques for managing blur, perspectives and layers of meaning.
02
From curve to cloud: meaning gains volume
When I talk about meaning, I can no longer think along a single axis. This is not a school exercise with an x and a y and nothing more. Meaning is built, and deformed, along at least three main axes:
- sign/vehicle: what we use to communicate – word, image, sound
- context/audience: where the sign moves, who reads, watches or listens to it, and with what expectations
- message/interpretation: what you think you are saying and what gets through
But that is not all: there is also time. The variable that sometimes changes everything, even when you thought you had arranged every part of your message down to the last comma.
From a multidimensional, multimodal perspective, that initial curve becomes a kind of living, three-dimensional cloud, constantly moving and changing shape. I call it the Gaussian Semiotic Cloud.
Inside it are all possible meanings, nuances, ambiguities, drifts and surprises. From outside it looks like chaos, beautiful to behold but hellish when you need to make sense of it. Look closely, though, and something remarkable emerges: it is not quite chaos. There are rules, a degree of causality, determinism and structured probability. It is within this cloud that meaning “precipitates” on contact with a real context. Only then does it become localised, readable and effective – or dangerous. That is why I became interested in this “shape”: if I can read it, perhaps I can also design it. And if I can design it, I can govern what happens when a sign enters circulation. Not always perfectly, not always predictably, but with greater clarity. And believe me, that makes all the difference.
03
Seeing the shape: from the “bell” to the “dynamic blob”
Just when you think you have grasped the concept and picture meaning following a neat bell curve, a regular distribution with a peak and two orderly tails, comes the surprise: it almost never works like that.
Let us start at the beginning. An isolated word, taken out of context and considered as a pure, abstract sign disconnected from speaker, listener and where they are, is often multimodal: it has several possible peaks of meaning. Alternative readings are already built into its code.
Take “transparent”: it can mean clear, honest and legible, but also fragile, exposed or vulnerable.
And what about “native”? Digital native, biologically native, native to a territory – each opens a different world.
Then there are even more common words that are far from harmless: “shrewd” can mean alert and astute, or sly and opportunistic.
“Practical” can mean efficient and concrete, but also hasty or superficial.
“Powerful” can evoke strength and authority, or conversely domination and abuse.
And words like “big”, “fast”, “safe” or “perfect”? They seem simple, but ask “Compared with what?” and the curve explodes. “Big” compared with whom? What? Yesterday? A competitor? These are relative meanings that become semantic landmines without a precise reference. Such words carry more than one meaning on their own, and they are often exactly the ones we choose to build an identity, a message or a promise.
When you immerse the word in a concrete context – an image, a sector, an interface, a narrative voice – something happens: multimodality collapses. It does not disappear, but concentrates on one or two prevailing meanings while the others become dormant. They remain hidden, ready to emerge as soon as “something” changes. This is semantic drift: a previously peripheral meaning becomes central, or vice versa.
04
Inside the Semantic Cloud
Within the Semantic Cloud, precipitation creates a “bubble” of meaning that is not a perfectly round, symmetrical sphere. It is more of a blob, a soft mass that deforms over time.
Some areas thin out, others expand. There are craters, ridges and layers. Then there are black holes: historical events, viral words, emotional shocks. True semantic attractors that bend space and cause meaning to migrate.
Let us look at some examples.
Words such as “propaganda”, once neutral or even positive – think of the “Sacra Congregazione de Propaganda Fide” – now carry a negative, manipulative aura.
Or “ideology”: once a sign of a structured worldview, now often synonymous with rigidity or fanaticism.
Or “viral”: first associated with disease, then a symbol of social media success, and ambiguous again after Covid.
Or “sustainable”: once noble, now often suspect through advertising overuse.
Semantic drift does not arise only from time. Sometimes a change of place, culture or sector is enough. “Powerful” is a compliment in a gym; in a romantic relationship it can sound threatening. “Light” is a plus in fashion, a problem in a strategic plan. Drift and precipitation depend not only on what you say but where and to whom. In the blob I call the Semantic Cloud, every change leaves a ripple. Some disappear; others remain and change everything. These shifts are often unpredictable: anomalies in historical development, extraordinary events, sudden explosions of trends. At other times they lie waiting, like hidden semantic traps ready to spring when you step on them. Loaded, dormant words seem harmless until the context reactivates them. When that happens, there is no escape: meaning has already migrated elsewhere.
Minimal but useful shapes and formulas
- Simple case (one peak): multivariate normal distribution → visually: ellipsoidal isosurfaces
- Real-world case (multiple peaks): a mixture of Gaussians → our dynamic blob
- In practice, think not in absolute definitions but in P(reading | context, time) – conditional probability.
Rather than defining a word, the task is to govern its field of possible interpretations according to where, how and when it will be read. Not a bell, but a blob. Not fixed, but deformable. And if you can see the shape, you can decide where to direct the precipitation.
Conclusion
Here I close my first conceptual framework: from bell to blob, from peak to tails. Next, we move into the workshop: how to make meaning precipitate where it is needed, through clear practical choices. I am looking for a simple way to bring the paradigm into focus, one piece at a time, one curve at a time.






























by myself.