Replace existing UI elements and add a new text file containing the Auction Guide. Replit-Commit-Author: Agent Replit-Commit-Session-Id: 069d4324-6c40-4355-955e-c714a50de1ea Replit-Commit-Checkpoint-Type: full_checkpoint Replit-Commit-Screenshot-Url: https://storage.googleapis.com/screenshot-production-us-central1/3df548ff-50ae-432f-9be4-25d34eccc983/069d4324-6c40-4355-955e-c714a50de1ea/9tQ591o
79 lines
3.6 KiB
Plaintext
79 lines
3.6 KiB
Plaintext
## Media Outlet Auction System Guide (Advertising Bidding Method Based)
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Here is a clean and structured English translation of the system guide, focusing on clarity and conciseness.
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---
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### 1. System Overview and Core Principles
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This platform is an innovative system that applies the **advertising bidding method** to the auction of media management rights.
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| Core Principle | Description |
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| :--- | :--- |
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| **Vickrey Auction** | The winner is the bidder with the **highest total score**. |
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| **Second-Price Payment** | The winner actually pays the price of the **second-place bid**. (Prevents excessive bidding) |
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| **Hybrid Scoring** | The final ranking score is calculated by combining **Bid Amount $\times$ Quality Score**. |
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| **Quality-Centered** | Evaluation prioritizes content quality, preventing simple price competition. |
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### 2. Core Mechanism and Ranking Calculation
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#### Final Ranking Score Formula
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$$\text{Ranking Score} = \text{Bid Amount} \times \left( \frac{\text{Quality Score}}{100} \right)$$
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#### Bidding Terms
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| Category | Details |
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| :--- | :--- |
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| **Bid Amount** | Minimum $\$100$ to Maximum $\$100,000$. Must be higher than the current top bid. |
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| **Management Period** | Default 30 days |
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| **Win & Payment** | The 1st place score wins but pays the **bid amount of the 2nd place score**. |
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#### Quality Score (1-100 points)
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| Score Range | Level | Key Evaluation Criteria | Quality Benefit |
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| :--- | :--- | :--- | :--- |
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| **71-100 pts** | **High Quality** | Excellent editorial standards, high user engagement, innovative content | Rank improvement, high rank with lower bids, increased exposure and engagement. |
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| **41-70 pts** | **Average Quality** | Meets standard criteria, stable content quality | |
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| **1-40 pts** | **Low Quality** | Below basic standards, low engagement, lack of consistency | |
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### 3. Auction Target Types
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Management rights for a total of **71** media outlets are up for auction.
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| Type | Count | Description | Minimum Bid |
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| :--- | :--- | :--- | :--- |
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| **People** | 24 | Personal branding, statements, profile editing rights for key figures. | $\$500$ |
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| **Topics** | 20 | Trend analysis, content curation for core topics, prediction market integration. | $\$300$ |
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| **Companies** | 27 | Corporate news, financial updates, corporate reputation management. | $\$1,000$ |
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\* The winner acquires **Exclusive Editorial Rights** to prioritize content decisions.
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---
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### 4. Strategic Bidding Guide
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#### 💡 Effective Bidding Tips
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1. **Prioritize Quality Score:** Improving the quality score offers a higher Return on Investment (ROI) than increasing the bid amount alone.
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2. **Analyze Competition:** Study past auction results and competitor bidding patterns in similar categories.
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3. **Gradual Bidding:** Increase bids step-by-step rather than making large jumps close to the deadline.
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4. **Consider Timing:** Competition often intensifies near the auction closing time.
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#### ⚠️ Mistakes to Avoid
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* **Ignoring Quality Score:** You cannot win with bid amount alone.
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* **Excessive Competition:** Emotional bidding can lead to losses.
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* **Short-term Thinking:** Don't neglect profitability relative to the management period.
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### 5. Technical Implementation (System Features)
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* **Real-time Processing:** Utilizes PostgreSQL for transaction management, ensuring concurrency control and real-time ranking updates.
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* **Security:** Features user authentication, bid data encryption, and a robust fraud prevention system.
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* **Data Analysis:** Machine Learning (ML) is used for **optimal bid suggestions**, and post-acquisition **ROI analysis** measures performance. |