Post3: The Ultimate Web3 Newsletter
Weekly insightful web3 reports powered by datasets that can be used to discover even further.
Twitter (aka X) is one of the main platforms to discover and engage with web3 content. Other social networks are joining the field such as Lens and Warpcast, a Farcaster client. While these platforms are excellent for staying up-to-date on your favourite projects, they are not great at showcasing new ones. This is because their algorithms tend to favour content from paid promoters or established communities, leaving many hidden gems on the shelves and hard to find.
While it’s possible for projects to eventually gain traction and visibility through promotion, it is known that in the cryptocurrency field, it pays off to be early. What if you could have access to new projects, airdrops and all sorts of crypto/non-crypto content at a weekly level?
If you’re a web3 enthusiast like me, you’ve probably heard of Mirror or Paragraph. These are the leading web3 publishing platforms that use the power of writing NFTs to generate revenue.
Post3 is a newsletter that shows the hottest projects in the ecosystem every week by collecting data from the Mirror website and Arweave. Not only you can follow the trends displayed in the weekly report, but also subscribe, mint and receive a copy of the dataset in your email inbox.
In this article, we will take a deep look into the weekly report insights that you can find in the newsletter but also engage with a tool that allows you to submit weekly datasets and discover even more content, just like a search engine.
👉 Join Post3 Discord community here. Follow Post3 on Twitter (aka X) and Warpcast
What is the problem with web3 publishing platforms?
While web3 publishing platforms are innovative and represent a potential future for online content creation, they face challenges to compete with their counterparts such as Medium and Substack. You can read more about the differences between web2 and web3 publishing platforms in the following article:
Let’s take a look at some of the current drawbacks of these platforms.
Lack of search engine
At the time I’m writing, none of the web3 publishing platforms have a built-in search engine, making it challenging to discover content beyond what’s showcased on their main pages.
There’s a website called Bress, that serves as a Mirror search engine, but it still lacks core features such as search by tags, timestamp and more.
Lack of data analytics
Another main issue with these platforms is their lack of data analytics. As a user, I like to have control of what is driving the community to mint, what kind of projects are generating the most revenue or even which layer 2 networks people are using to mint.
In addition, solutions to get insights from textual data are also in need, such as discovering what languages are the most used, the average length of articles’ bodies and simply wordclouds that showcase the most used keywords in a certain timeframe.
Lack of permanency
If Mirror or Paragraph disappear, where my writing NFT will be stored? To answer this question we need to understand what is a writing NFT. When the author publishes an entry on these platforms, they have the option to upload it on Arweave as a JSON file. This is crucial because Arweave permanently stores the data, not the platform itself.
The writing NFT surges when someone mints the article on one of the platforms, and they can easily access the link from their wallets, but there’s no proven guarantee so far that they will have access to the JSON file submitted on Arweave if the platform goes down.
Hence, users should be able to navigate the Arweave space with ease and find their articles in JSON format, in case they want to migrate this information to other platforms in the future.
What can you find in the Post3 newsletter?
Post3 is a web3 newsletter that is delivered weekly on Mirror. Each article is an insightful report powered by a dataset. This data is extracted from Arweave and the Mirror website using GraphQL and Web Scraping techniques.
The weekly reports contain several sections with charts and tables that are useful for understanding market trends. You can see the report from week 18 2024 as a reference below:
Let’s now analyse the sections one by one.
General Statistics
This section provides a table summarizing key statistics about mints and revenue. It includes metrics like total volume (everything minted), average mint value (mean), typical mint value (median), and spread of mint values (standard deviation). By analyzing these statistics together, you can gain a better understanding of the overall health and trends of the Mirror platform.
User Activity
This chart tracks both the number of mints and collections revenue by weekday. This lets you see which days tend to have the most activity, helping you plan your next article submission for optimal engagement.
Authors/publications with the most collections
This chart highlights the top authors or publications based on the number of mints they got. This chart can help you to:
- Discover the most active and potentially successful creators.
- Suggest a potential saturation in a specific project.
- Discover new projects in the market.
Most collected entries
This chart showcases the articles or entries with the highest number of mints. Below the chart, you’ll find a detailed list where each article title corresponds to its respective number in the chart. This chart can help you to:
- Analyze the types of writing NFTs that people mint the most.
- Find correlations between specific subjects, the number of mints and revenue.
- Easily explore the top content from Mirror.
Authors/publications with the most revenue
This chart is similar to the “most collections” one but focuses on the articles or entries that have generated the most revenue, instead of the number of mints. This chart can help you to:
- Find correlations between revenue and the number of mints.
- Understand why few mints can generate high revenue, and why people are willing to spend it.
- Analyse the most valuable authors/publications.
Entries with the most revenue
This chart is similar to the “most collected entries” one but it is focused on the entries that generated the most revenue. Sometimes the number of mints and revenue are aligned, but this is not always the case. This chart can help you to:
- Analyze the types of writing NFTs that people are willing to buy.
- Find correlations between specific subjects, the number of mints and revenue.
- Explore premium content from Mirror.
Network Usage
You can mint writing NFTs in different layer 2 chains, such as Linea, Zora, Optimism and Base. This pie chart provides transparency to users about the network usage on Mirror, allowing you to:
- Investigate whether there’s been a change in which networks are most popular for NFT minting
- Decide which network to use based on their growth on Mirror.
Datasets
At the end of the report, you’ll find a section showing the features that compose the dataset that powered the analysis:
- platform: web3 publishing platform.
- title: the title of the article.
- description: a short description of the article.
- body: the full content of the article.
- link: the URL for the article.
- arweave_link: the URL for the Arweave JSON content.
- author: the author/publication.
- contributor_link: the writer of the article.
- date: the date when the article was first published.
- tags: tags that define the article generated using LLMs.
- collections: number of mints the article has at the time the data was extracted.
- supply: the maximum number of mints an article can have.
- price: the price of the article in ETH or MATIC depending on the currency feature.
- price_usd: the price in USD.
- currency: either MATIC or ETH, others may join in the future.
- network: the L2 solution used to mint the article.
- revenue: collections times the price in USD.
This dataset contains all the information from the week, allowing data analysts to do their own research. Nevertheless, you can also use Post3 Engine and discover more charts and content without analytical skills. We’ll learn more about Post3 Engine in the following section, meanwhile, you can download the following dataset as an example.
To obtain a dataset, you need to mint a report and subscribe to Post3 on Mirror. Once you’ve completed these steps, I will manually send the dataset to your email inbox, it could take up to 24 hours for me to share it. This process may be easier in the future depending on adoption.
👉 Join Post3 Discord community here. Follow Post3 on Twitter (aka X) and Warpcast
What can you do with the datasets?
Post3 datasets aim for all sorts of applications. Data enthusiasts are familiar with data manipulation, hence they can easily explore the datasets and grab information tailored for their needs. The applications can be the following:
- Create dashboards: You can make charts like the ones in the Post3 weekly newsletter and seamlessly integrate them into web applications for writers and users.
- Develop chatbots: With the body of the articles, developers can apply cleaning strategies, vectorise the content and save it in a vector database. Finally, they can feed LLMs to make chatbots that provide insightful summaries of the articles.
- Make predictions: By using techniques like exploratory data analysis and machine learning, you can extract knowledge from the data and use it to forecast future trends.
Ok, this is all great, but what if you are not a data steward? That’s where Post3 Engine comes in.
On this platform, you can upload a dataset, and pick one of the following models.
Explorer
Think of it like like a search engine. You can enter keywords or topics, and the system will find up to 30 relevant articles. For example, searching for “Airdrop” would show you articles that directly mention Airdrop or discuss closely related concepts.
Then you can just click on one of the boxes, and it will redirect you to the article’s URL. See below the first article on the list:
Collections & Revenue
This interactive model uses the charts from the reports but offers more engagement with dynamic bar and pie plots. You can also specify the week’s range and visualise the charts only within that period.
Textual Analysis
This model uses dashboarding to show textual insights from the dataset. Explore metrics such as the top languages used during the week, word clouds, and the average length of bodies, descriptions, and titles.
With the above chart, you can identify countries with high engagement on the Mirror platform.
- Platform owners can develop targeted marketing strategies to retain these users
- Writers can make content tailored to these communities, driving greater adoption and growth.
Another interesting chart is the textual lengths one.
Writers and platform owners can gain valuable insights from these box plots, which reveal the average character count for bodies, descriptions, and titles.
What’s next?
While Post3 has made significant progress, there are still opportunities for expansion and improvement. For example, the newsletter could be developed into multiple formats, each tackling specific areas of interest such as revenue and collections, tags/keywords and textual data.
The same applies to Post3 Engine, which has the potential to evolve beyond its current role as a basic gateway to submit datasets and retrieve valuable insights. Enhancements to the user experience and interface could make the platform more intuitive and user-friendly while integrating additional models and features.
Paragraph as recently acquired Mirror, which may result in changes in the Mirror’s website, leading to modifications in the data extraction process implemented by Post3. However, these backend modifications won’t impact the final goal of the web3 newsletter and hopefully, it will make it even richer.
This project relies on user adoption to grow, If you’re excited about its potential, consider minting a report and subscribe. This small contribution grants you access to valuable datasets delivered to your email inbox. These datasets put you at the forefront of web3 exploration.
👉 Join Post3 Discord community here. Follow Post3 on Twitter (aka X) and Warpcast
