The Suspended Mall:
——Artificial Nostalgia and Imagined Personal Memory
This research takes Svetlana Boym’s The Future of Nostalgia as its primary theoretical point of departure. Boym treats nostalgia as a historical affect of modernity: a longing for a “home” that no longer exists—or may never have existed. She distinguishes between “restorative” and “reflective” nostalgia to map, on the one hand, nostalgia’s susceptibility to political manipulation, and on the other, its aesthetic and ethical potential, tracing how it appears across urban memory, popular culture, and experiences of exile. Her framework can be partially extended into the era of mobile internet and generative AI. In citing Boym, this study mainly draws on her distinction between reflective and restorative nostalgia, as well as her description of how nostalgia forms a double-exposure relationship between past and present, reality and imagination. Building on this, the feed mechanisms of 2010–2020 and the generative-model mechanisms of 2022–2030 are treated as structural shifts in how nostalgia is triggered, and the research further discusses how “artificial/imagined personal memory” is produced, circulated, and claimed within contemporary visual culture and social media ecosystems.
Other-Side Research of Mall Nostalgia：
0. What exactly is the research object?
This research is not about nostalgia as a general emotion, but about a more specific chain of phenomena:
When nostalgia no longer comes only from remembering, but from a manufactured feeling of remembrance.
Mobile internet: nostalgia becomes an emotion that is pushed to you, looped, and socially validated.
Generative AI: nostalgia further becomes images and narratives that are producible, privately customizable, and forgeable as “personal memory.”
“Artificial / Imagined Personal Memory” can be defined as:
An image/scene that is experienced as if it were personal memory, yet does not come from lived experience, but from models, templates, training data, and visual grammar.
It can be either:
Imagined: it “feels familiar since childhood,” yet never happened in reality (the paradox of “I return to a home I have never been to”).
Artificial: it is not completed by one’s own imagination; instead, the model replaces imagination and feeds the result back as a ready-made sense of memory.
1. Three-era structure: the core conclusion of the comparison table
| Dimension | Boym’s Nostalgia Structure (2001) | Mobile-Internet Nostalgia Structure (2010–2020) | AI Nostalgia Structure (2022–2030) |
|---|---|---|---|
| How nostalgia is triggered | Triggered by lived experience (individual) | Triggered by algorithmic pushes (the feed) | Triggered by model generation (externalized unconscious) |
| Object of nostalgia | The real past; the unrealized future | An image-based past; cultural memes | A generatable “fictional past” |
| Nature of memory | Fragmented, but grounded in real life | Hyper-fragmented, decontextualized | Reality and fiction fully mixed (overflow) |
| Definition of virtuality / VR | Multiple planes of consciousness | Mediated experience + social networks | A generatively simulated world |
| Collective memory | Shared landmarks (public space) | Shared images (memes, short video) | Shared models (a common AI training set) |
| Affective driver | A response to rupture and speed | A response to overload and immersion | A response to identity and the plasticity of reality |
| Function of nostalgia | Self-reflection; identity continuity | Emotion regulation; community belonging | Reality re-making; visualization of the unconscious |
| Risks of nostalgia | Becoming a tool of nationalism | Becoming an algorithm-driven emotional loop | Becoming generative politics and historical falsification |
| Agency of nostalgia | Nostalgia arises from within (reflective) | Nostalgia arrives via external pushes (triggered) | Nostalgia emerges from unconscious structures you don’t notice (predictive) |
This comparison can be compressed into a single axis: a shift in mechanism.
1) The power to trigger nostalgia shifts from “me” to “the system”
Boym (2001): nostalgia is mainly triggered by individual experience (a place, a smell, a sudden hit).
Mobile internet (2010–2020): nostalgia is triggered by the feed—before you even begin to recall, the content has already arrived.
AI (2022–2030): nostalgia is triggered by generation—you have never seen it, yet when it appears it “feels remembered.”
2) The nostalgic object shifts from “the past” to “a past that can be generated”
The past is no longer history, but a visual grammar: color grading, grain, camera language, spatial templates, display aesthetics.
As a result, the object of nostalgia can slide from “true memory” to “fictional but convincing memory.”
3) The unit of collective memory changes: landmark → image → model
Boym emphasizes that collective memory is closer to everyday landmarks and shared ways of living than to national narratives; collective memory is more like a shared “potential space / playground.”
The internet transforms “shared landmarks” into “shared images” (memes, short videos, templates).
AI further transforms “shared images” into “shared models”: what is shared is not just the picture, but the statistical structure of training data (a kind of collective visual unconscious).
2. Boym’s “skeletal concepts” that can be applied directly to mobile internet and AI
A) Reflective vs. restorative: not a difference in emotion, but a difference in narrative mode
Boym’s distinction can serve as an underlying classifier for the three-era shift:
Restorative nostalgia: treats the past as a “perfect snapshot,” wants to repair it, return to an “original truth,” and does not allow traces of decay.
Reflective nostalgia: accepts irreversibility and fragments; it is drawn to distance and process, and can even include humor and irony.
In the present, this means:
Mobile internet can push many forms of reflective nostalgia toward a restorative addictive loop (because the feed keeps supplying “perfect snapshots”).
AI offers stronger “repair power”—not only snapshots, but continuous serial narratives, completions of missing parts, and versions of what “never happened but should have.”
B) Nostalgia as “sideways looking”: it never stares straight at history
Boym argues nostalgia is not literally going back, but “looking sideways.” When one tries to turn the past into a single, frontal, restorable object, mimetic reconstruction often occurs—remaking the past into the present or into a desired future.
This is almost a gloss on AI nostalgia:
The strength of generative nostalgia is mimesis: it is not evidence, but the illusion of “looking like.”
What it satisfies is not historical truth, but “visual similarity + emotional similarity.”
C) “VR” is not technology, but a multi-layer plane of consciousness
Drawing on Bergson, Boym suggests reflective nostalgia can awaken multiple planes of consciousness; the “virtual reality” of consciousness does not depend on technology—it belongs to human imagination and freedom.
AI’s move here is: turning what once belonged to inner consciousness—this multi-plane double exposure—into externally visible, shareable, mass-generatable images.
D) “Potential space”: collective memory is not a cemetery, but a playground
Boym cites Winnicott: cultural experience exists in a “potential space” between the individual and the environment, supporting creativity like play rather than suppressing it.
So AI nostalgia is not only a question of true/false; it also involves:
how it becomes a space where people “play” with identity, time, and belonging;
and how that space is, in turn, shaped by platforms and models.
3. Mobile-internet nostalgia: the feed turns nostalgia into an “instant commodity”
If Boym discusses nostalgia under the ruptures of modernity, then in the mobile-internet era we see:
1) Nostalgia becomes “auto-triggered” and forms an affective loop
Feed mechanisms make “distance” hard to form; nostalgia no longer waits for time to sediment, but becomes a real-time compensation system.
Nostalgia no longer needs twenty years of fermentation—it becomes “nostalgia for yesterday, starting today.”
2) The unit of circulation becomes “fragmentary visual grammar”
No complete story is needed—only a combination: corridor lighting + ceiling grids + low saturation + emptiness + a certain period texture, and the feeling of “as if I remember” can be activated.
3) “Core” aesthetics turn fragmented sense of era into poetry
TikTok styles like corecore—an “anti-trend” montage aesthetic—use fragments and collage to express overload, disorder, and rupture. It is almost an “affective double exposure.”
4. AI nostalgia: why it is “more dangerous and more seductive”
The core upgrade of AI nostalgia is the “externalization of the unconscious,” which can be broken into four mechanisms:
Mechanism 1: from a “pushed past” to a “synthesized past”
Mobile internet gives you other people’s old photos; AI directly generates old photos that do not exist but feel credible.
Key changes:
the nostalgic object no longer needs a real referent;
“memory-feeling” becomes a producible material.
Mechanism 2: from “shared images” to “shared memory statistics of the model”
A “shared model” (a shared AI training set) means:
what is shared is not the same photo, but the same statistical rule of “what a photo should look like.”
This explains why different people can have similar affective responses to the same class of AI retro images: what is hit is a shared visual template, not a shared experience.
Mechanism 3: from “remembering something” to “being persuaded that I remember”
AI can generate scenes never lived yet instantly “claimable” as memory—especially when it uses widely shared childhood symbols and spatial templates (classrooms, malls, playgrounds, old TVs, KFC-style tiles, etc.).
This is a new kind of memory experience:
not recall, but
adoption: taking a synthetic image as “something that has always been inside me.”
Mechanism 4: from “nostalgia” sliding toward generative politics and historical falsification
AI makes “the past” editable. When nostalgia shifts from a private emotional tool into a scalable “historical-style generator,” it enters a more dangerous zone (propaganda, identity mobilization, fabricated evidence, historical re-narration).
5. A present-day phenomenon map: the social-media ecology that supports AI nostalgia
Online aesthetics such as liminal/mall/dreamcore form a clear “soil map” for AI nostalgia. Below are observable and citable nodes:
A) Dead Mall / Liminal Mall: a “spatial double exposure” of nostalgia
The Reddit community r/deadmalls focuses on photos, videos, and discussion of dead/dying/abandoned malls.
https://www.reddit.com/r/deadmalls/
Dan Bell’s Dead Mall Series on YouTube is a long-running representative of “ruin-gaze” toward malls.
https://www.youtube.com/playlist?list=PLNz4Un92pGNxQ9vNgmnCx7dwchPJGJ3IQ
Its affective force comes from a built-in double exposure: the lights are still on, but the crowd is gone; the structure is familiar, but the function is dead.
B) Liminal Space: empty, overexposed, overly bright or overly dark public spaces
In online contexts, “liminal space” is often described as places that should be lively but are strangely vacant, producing eeriness, familiarity, and surreal affect. The Backrooms is a canonical liminal-space narrative, and in recent years it has intersected with analog horror.
Instagram
https://www.instagram.com/liminalmoods/
https://www.instagram.com/liminal.spacee/
https://www.instagram.com/liminal.space.s/
https://www.instagram.com/aaaaaagghhhhhhh/
https://www.instagram.com/liminal.bot/
https://www.instagram.com/liminalsp8ces/reels/
https://www.instagram.com/liminal_spaces_acc/
C) Dreamcore / Weirdcore: templating “dreams that feel like memories”
Dreamcore is often described as a TikTok-popular dream aesthetic that frequently touches childhood objects and unease.
Weirdcore often mixes nostalgia with disorientation through lo-fi, uncanny edits—like fragments of a memory you can’t fully name.
These aesthetics are directly tied to AI nostalgia: they are already a “nostalgia grammar” that models can learn, and therefore the easiest to replicate at scale with AI.
Instagram — Dreamcore
https://www.instagram.com/dreamcoreclub/
https://www.instagram.com/dreamcore.png/
https://www.instagram.com/http.dreamcore/
https://www.instagram.com/rkur/
Instagram — Weirdcore / Dreamcore hybrid
https://www.instagram.com/weirdcore.dreamcore/
https://www.instagram.com/weirdcoretv/
https://www.instagram.com/we1rd.me4t/
https://www.instagram.com/n0stx.lgix/