This entry is part of the series: Paragraph Articles Analysis. Each week, Post3 utilizes data extraction and data analysis techniques to deliver insightful reports with information concerning authors, articles, revenue, chains, keywords, and more, derived from exploring Paragraph data.
For Week 49, we tackle the following questions:
Who are the authors from whom people have collected the most?
Which articles were the most collected?
Which authors generated the most revenue?
Which articles generated the most revenue?
What was the networks/chains usage?
Who caught our attention this week?
The number of collections/mints of some articles might have changed at the time I’m writing.
These are only the posts that were submitted on Arweave, all the others are not being taken into account for the analysis.
Let's begin to analyse 252 articles collected from Week 49.
1 - Who are the authors/publications from whom people have collected the most?
The number of times an article has been collected/minted serves as a valuable metric to understand an author's popularity on Paragraph. The “Author“ is the publication/newsletter, some authors such as protocols and ecosystems have several contributors that write to their publications. Let’s take a look at the top 10 authors whose work has attracted more collectors.
The revenue is set to USD because Paragraph Articles are paid in both ETH and MATIC. Both Cryptocurrencies were converted to USD using an API for better visualization.
In the bar chart @nacionbankless dominates with the most collections and revenue. This Spanish publication had more than 45 collections at the time I'm writing. @aley.eth won second place, with his first article on Paragraph. Finally, with slightly fewer collections is @hellno.
Below is the list of the Authors with the most collections on Week 49:
2 - Which articles were the most collected?
Some authors publish several times on a weekly period, which grants them more collections than others. But we need to take a look at articles individually, to see which ones perform better. These are the top 10:
Investing in Ethereum? Why Hardware Wallets are a Beginner's Best Friend
IS PRIVACY IMPORTANT TO YOU?
INTRODUCING "RAILGUN" - Private & Anonymous DeFi
@aley.eth's first article on Paragraph, about wallet security, granted him the first place, with the most mints/collections. A new integration to Farcaster (herocast), won 2nd place. Articles 3, 4, 5, 6, 7 and 8 got all the same number of collections.
3 - Which authors generated the most revenue?
Revenue serves as an indicator of one's ability to attract and retain people to mint their content. Here we’ll take a look at the top 10 authors that generated the most revenue from minted articles, and how it correlates with collections.
We've seen at the beginning that @nacionbankless got the most collections and revenue for week 49. It clearly dominates the chart. @henrypye and @avc generated the same revenue with the same amount of collections. This chart shows clearly that not every week the collections correlate with revenue. @aley.eth for instance has a lot of collections but less revenue than others with way fewer collections.
Below is the list of authors with the most revenue:
4 - Which articles generated the most revenue?
Just like in collections, revenue must be studied individually. People might be loyal to their favourite authors, but in the end, they will mint what they really like or find useful. Studying articles individually is important for writers to understand what kind of content people are willing to mint, and at what price. Below, are the top 10 with the most revenue:
The top articles generated the same revenue, around 25 USD with the same number of collections. Two of these articles are from @nacionbankless, other is from @henrypye about making art with algorithms and finally @avc with his article about monetizing protocols.
5 - What was the networks/chains usage?
Understanding the usage of L2 chains for minting NFT articles, is key for writers to decide which network should they use. The following pie chart only compares the usage, other metrics should be taken into account, such as the type of articles that are being published in each chain and so on.
Base dominates in Paragraph with 66.4 % of usage. Followed by Polygon with 18.8 % and Optimism with 6 %. Marketplace (4 %) stands for the articles that are no longer available to mint on Paragraph, but they are available at NFT Marketplaces. Zora has 2.7 % and Ethereum 2 %. Surprisingly there are still 2 % of writers opting to upload their articles on L1.
6 - Who caught our attention this week?
Post3 looks at several catching titles from the sample gathered and takes a deep read into the content. There’s no particular field that Post3 prioritises, we embrace all topics. Let’s see who caught our attention this week:
About SheFi: Wild Futures with Maggie Love in @ensdao
Fiat currencies: Fiat is Dead in @decentralizedsoul
Energy Web Token (EWT): Energy Web Token (EWT) – energy on the blockchain!
in @altcoinanalystIn Portuguese: IA além do hype: como a tecnologia possibilita muito mais do que a criação de imagens in @spotlink
Sci-Fi vibes: Humans and Machines: A Future of Collaboration or Disconnection? in @dreitberg
There’s no particular order in the articles mentioned before. There is much more interesting content in the dataset, which Post3 delivers to you in the form of NFT data. Let’s see how you can access it in the following topic.
7 - Accessing Week 49 Paragraph Dataset
Post3 encourages you to explore the dataset and uncover more gems or generate your own charts and insights. It is available at the Ocean Market, which is a web3 data marketplace brought by the Ocean Protocol.
The dataset contains the following features:
platform: in this case is Paragraph
arweave_link
link: Paragraph URL
title
preview
subtitle
categories: tags used
contributor: the person who wrote the piece
date
collections: number of collections
supply
price
currency
network
author: newsletter/publication
revenue
You can find it here.
Final Notes
With your support, Post3 can expand the scope of the weekly analysis and bring broader insights such as textual analysis and comparisons with previous weeks. To learn more about Post3's mission and how it intends to contribute to the Web3 Publishing ecosystem, please refer to the following entry:
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