Aydın Tiryaki and Gemini AI

Abstract: Current digital video publishing pushes the limits of sustainability with its file-duplication-based methods and structures that fail to fully protect creator rights. This article proposes a new, ecological, fair, and auditable publishing protocol that transforms video from a physical file into a “virtual asset” that can be referenced, aiming to solve data waste and attribution injustice.

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1. INTRODUCTION: THE SHIFT FROM A FILE-BASED INTERNET TO AN ADDRESS-BASED NETWORK

In today’s video platforms (such as YouTube), sharing or quoting a short segment of content requires copying the original video, re-processing it (rendering), and uploading it as a new file (e.g., Shorts/Clips). This “Copy-Process-Upload” cycle increases global data storage costs, leads to significant energy waste, and often severs information from its original source.

The proposed model aims to radically change this structure through “Virtual Segmenting” technology. The goal is not to duplicate data, but to manage the address of the data and to share meaning without stripping it of its context.

2. TECHNICAL INFRASTRUCTURE AND ECOLOGICAL SAVINGS

2.1. File-Less Sharing: The “Virtual Clip/Citation” Protocol

In the new system, a “Citation” is not an independent MP4 file, but a metadata command pointing to specific time intervals of the master video.

• Mechanism: When a user selects the segment between the 10th and 15th minutes of a video, the system does not create a new video. It simply records the data: [Source ID + Start: 10:00 – End: 15:00].
• Zero Render: No processing power is consumed, and no file transfer occurs. Millions of citations occupy only as much space as a few kilobytes of text files.

2.2. Hybrid and Multi-Source Assembly

The system allows for the simultaneous merging of data streams from different sources, not just a single video.

• Audio/Video Separation: A user can take the visual stream from “Video A” and overlay the audio stream from “Video B”. This process happens virtually in the player, not in editing software.
• Unlimited Compilation: Segments from 10 different experts’ videos can be appended to create a “Virtual Symposium” or “Virtual Documentary” without uploading a single new file.

3. ETHICAL STANDARDS AND CONTEXT SECURITY

Systemic measures are introduced against “cherry-picking” (taking out of context) and manipulation, which are major problems in digital media.

3.1. The 60-Second Rule (Minimum Context Limit)

To preserve the integrity of an idea, a minimum duration limit must be applied to citations.

• Rule: A “Virtual Citation” must be at least 60 seconds long.
• Purpose: To prevent the distortion of meaning by cutting off the logical connectors (like “However,” “But,” or “Because”) used by the speaker.

3.2. Fair Use Quota (Percentage Upper Limit)

To prevent labor theft and encourage viewers to visit the main source, upper limits must be defined.

• Rule: The entirety or a very large portion (e.g., more than 20%) of a video cannot be shared as a single citation block.
• Restriction: A curator can make a limited number of citations (e.g., maximum 3) from the same video.

3.3. Redefining Remix Permissions

The “Remix Permission” on current upload screens should evolve from a “blank check” into a “Smart Contract.”

• The content owner should be able to select options such as: “Allow video only,” “Allow audio only,” or “Allow only in approved contexts.”

4. AUDIT, APPROVAL, AND ACCESS MANAGEMENT

4.1. Approved Reference List

Content creators must have full control over their digital legacy. Others may cite the video, but the creator decides whether these citations appear on their own profile.

• Mechanism: The creator receives a “Pending Citations” notification. High-quality citations that reflect the correct context are approved; manipulative or low-quality ones are rejected/hidden.

4.2. Multi-Layered Privacy Settings

Virtual citations should have privacy levels just like physical videos:

• Private: Research notes taken by the individual for themselves.
• Unlisted: Special segments shared only with a specific workgroup.
• Public: Published and approved references.

5. ECONOMIC JUSTICE AND STATISTICS

5.1. Fair Attribution Model

In the current system, the person making the copy gets the views. In this model, when a “Virtual Citation” is watched, the traffic flows to the original source.

• Operation: When a viewer watches a compilation consisting of 10 different videos, the system opens 10 different “micro-sessions” in the background. The view count (+1) and watch time for each segment are credited, second by second, directly to the owner of the original video.

5.2. Impact Analytics and “Citation Statistics”

The metric of success should not just be “view count” but “reference value.”

• New Metrics: The user dashboard should include data such as “How many times were my videos cited?” and “Which seconds were referenced the most (Heatmap)?”, measuring the intellectual impact of the creator.

6. USER EXPERIENCE (UX) AND INTERFACE

6.1. New Profile Tab: “Citations”

A “Citations” tab should be added to the YouTube channel structure, alongside “Videos,” “Shorts,” and “Live.” This tab functions as a space for “Knowledge Curation,” independent of duration limits (unlike the 60s limit of Shorts).

6.2. Frictionless Source Navigation

The viewer must be able to reach the source of the information effortlessly.

• Interactive Logo: A dynamic logo/icon indicating the owner of the currently playing segment should appear in the corner of the screen.
• Seamless Transition: When this logo is clicked, the original video should open in a new tab starting exactly at that second, without stopping the current video.
• Embedded Bibliography: A list of all sources used, with timestamped and clickable links, should be automatically generated in the video description or at the end.

7. APPLICATION DOMAIN: VIRTUAL CITATION AND REFERENCE MANAGEMENT WITHIN THE YOUTUBE ECOSYSTEM

The YouTube ecosystem represents the most viable and applicable “laboratory” for the theoretically constructed “Virtual Citation and Reference Architecture.” With its existing metadata structure, segmenting features, and massive content repository, YouTube already possesses approximately 80% of the technical infrastructure required for this model. The following points outline how this model can be implemented using current YouTube interface terminology:

7.1. Transformation of the “Description Box” into a Dynamic Bibliography

The existing YouTube “Description” area can be evolved from a simple text box into the “Dynamic Citation Panel” proposed in the manifesto.

• Timestamped Links: Current 00:00 format links can be utilized as “Virtual Clips” to direct viewers not just to sections within the same video, but to specific seconds of external videos from other channels.
• Clickable Attribution List: A dedicated “Sources used in this video” section within the description allows viewers to reach the original content in a new tab without any friction.

7.2. Using the “Chapters” Feature as Virtual Boundaries

The “Chapters” feature on YouTube’s progress bar is the ideal tool for implementing the proposed “60-Second Context Rule.”

• Virtual Segments: A content creator can mark an excerpt cited from another video as a “Chapter” on their own timeline.
• Source Labeling: When a viewer hovers over this chapter, a label automatically displaying the original video title and the creator’s name can appear.

7.3. Evolution of “Remix” and “Clip” Features

YouTube’s current “Remix” and “Create Clip” tools are primitive prototypes of this vision.

• Data Efficiency: The current “Clip” feature already shares a link without creating a new file. Our proposed “Virtual Citation” structure integrates this with a “Publish” option, allowing the citation to be presented as a standalone piece of content on the user’s channel.
• Hybrid Editing: A “Reference Layer” added to the YouTube Studio “Editor” would allow creators to virtually drag and drop audio or video streams from other videos onto their timeline while uploading.

7.4. “YouTube Studio Analytics”: The New Metric of Success

The YouTube data analysis dashboard is the most suitable environment to integrate the proposed “Citation View Count” statistic.

• Impact Analysis: Under the “Reach” tab, creators can monitor metrics such as “Total watch time generated via virtual citations of your video” and “External channels where your video is referenced” through second-by-second heatmaps.
• Fair Crediting: The analytics panel automatically credits view counts (+1 View) to the original owners by segmenting the session data accordingly.

7.5. Channel Interface: Integration of the “Citations” Tab

Adding a “Citations” tab alongside “Videos,” “Shorts,” and “Live” transforms the platform from a mere streaming site into a global knowledge archive.

• This tab functions as a Digital Reference Library, listing the user’s “Virtual Compilations” as well as the “Approved Citations” others have made from their original work.

CONCLUSION

This proposed model transforms the internet from a “copy-paste dump” into an organic “Knowledge Network” where every piece of data is interconnected, labor is protected, and waste is prevented.

In this system, curating existing content with the correct context is as respectable a form of production as creating new content. The future of digital publishing must be built on this architecture that manages meaning and addresses, not files.

Concept and Design: Aydın Tiryaki

Technical Analysis and Compilation: Gemini AI

Date: December 20, 2025

APPENDIX 1: TECHNICAL METHODOLOGY AND SYSTEM ARCHITECTURE REPORT

The theoretical framework and final documentation of this study were realized through a strategic Human-AI Collaboration, utilizing three distinct operational layers of the Gemini ecosystem, optimized according to specific task requirements:

1. Analytical Modeling and Logical Validation (Deep Thinking Mode): The foundational technical concepts, ethical guardrails, and the architecture of “Virtual Segmenting” were developed using Gemini’s Deep Thinking mode. In this phase, the logical consistency of the proposals was audited, and in-depth analyses were conducted to ensure the system’s compatibility with modern software architecture and data management principles.

2. Semantic Synthesis and Multilingual Academic Output (Paid/Pro Tier): For the consolidation of all technical data into a professional manifesto and its subsequent high-fidelity translation into English, the Gemini 3 Flash Pro tier was utilized. This layer leveraged an expanded context window to integrate complex ideas into a unified structure, ensuring terminological precision and a rhetorical tone aligned with global publishing standards.

3. Operational Finalization and Iteration (Flash Mode): The final review of the documentation, rapid adjustments, and concluding iterations were handled via the Flash mode. This phase focused on latency optimization, ensuring a seamless and high-speed completion of the workflow and final response cycles.

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A Note on Methods and Tools: All observations, ideas, and solution proposals in this study are the author’s own. AI was utilized as an information source for researching and compiling relevant topics strictly based on the author’s inquiries, requests, and directions; additionally, it provided writing assistance during the drafting process. (The research-based compilation and English writing process of this text were supported by AI as a specialized assistant.)