How to distinguish input and output: Analysis of hot topics on the entire network in the past 10 days
In the era of information explosion, how to distinguish input (obtaining information) and output (creating content) has become the key to efficient learning and work. This article combines hot topics on the Internet in the past 10 days and explores this topic through structured data analysis.
1. The core difference between input and output

Input is the process of receiving information, such as reading and listening to lectures; output is the expression of information after processing, such as writing and creation. The following is a classification of hot topics in the past 10 days:
| Type | typical content | heat index |
|---|---|---|
| input type | OpenAI conference analysis | 9.2/10 |
| Output type | AI Painting Creation Competition | 8.7/10 |
| hybrid | ChatGPT application case sharing | 9.0/10 |
2. Top 5 popular input contents
| Ranking | topic | platform | average daily searches |
|---|---|---|---|
| 1 | OpenAI new model released | Twitter/Zhihu | 1.2 million+ |
| 2 | World Cup Match Analysis | Douyin/Hupu | 950,000+ |
| 3 | Double 11 consumption report | Weibo/Xiaohongshu | 870,000+ |
| 4 | Winter epidemic protection guide | WeChat public account | 650,000+ |
| 5 | Musk’s latest interview | YouTube/Bilibili | 580,000+ |
3. Top 5 popular output contents
| Ranking | Content form | Typical cases | Interaction volume |
|---|---|---|---|
| 1 | AI generated video | Pika1.0 portfolio | 3 million+ |
| 2 | Technical Tutorial | StableDiffusion Advanced Guide | 1.8 million+ |
| 3 | Hot comments | Analysis of Dong Yuhui’s Short Composition Incident | 1.5 million+ |
| 4 | UGC challenge | #10yearsComparisonChallenge# | 1.2 million+ |
| 5 | Open source projects | Llama2 fine-tuning solution | 900,000+ |
4. Input-output transformation methodology
According to popular content analysis, efficient conversion needs to follow the following principles:
1.5:3:2 Rule- 50% time input, 30% time thinking, 20% time output
2.Hotspot response cycle- Analytical content is best produced within 24 hours after a major event occurs
3.Content upgrade path: Original information → Knowledge cards → Mind map → Complete work
5. Comparison of content characteristics of typical platforms
| platform | Input features | Output features |
|---|---|---|
| In-depth long text reading | Light sharing in Moments | |
| Douyin | Fragmented information flow | Short video creation |
| Zhihu | Professional Q&A community | Column article output |
| Station B | course study | UP main content production |
Conclusion:In an information environment dominated by algorithms, proactively building a closed loop of "input-processing-output" is an effective way to avoid information overload and achieve cognitive upgrades. It is recommended to set aside dedicated time every day for systematic output and transform hot information into personal knowledge assets.
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