Analyzing Cryptocurrency Articles Through Diffbot

The world has already slowly been going digital, but the stay-at-home restrictions have quickened their pace. Because a lot of individuals derived another means of earning online one notable tech trend that saw a rise in interest in blockchain technology — the blockchain technology caught the interest of many during the lockdown periods. A lot of articles were written on various cryptocurrencies which include popular ones like Bitcoin, Ethereum, and lots more. As many saw its importance, they tended to invest in it. A lot of others saw that these crypto coins are the future so are in search of information on the best cryptocurrency to invest in. Blockchain technology has numerous uses.  Some of its uses include smart contracts, DLT solutions, and NFTs. If you are looking for an advanced solution with blockchain technology development, we would recommend this domain. For others, let’s dive deeper into the most popular use of blockchain is cryptocurrency.


The boom of cryptocurrency can be seen in the millions of articles and papers published about it. If you’re looking to deepen your understanding of crypto, my favorite publications will be mentioned below. As you know there is a lot of information about cryptocurrency online. Some are relevant while most are irrelevant.  Fortunately, some tools help narrow down relevant information. One of which is natural language processing. The natural language processing (NLP) tools can make it easier to find the relevant information — as well as gain valuable insights from them.

There are various use-cases for this. As an example, if you’re a company involved in a fintech business, you can use NLP to scour info online on what people say about you and your competitors. And how you can improve yourself to beat your competitors. Meanwhile, if you’re an investor, you can also use the NLP to analyze updates about certain companies and cryptocurrencies to make informed decisions regarding investments. Do not make any wrong move when investing. If you are just starting an investigation into how blockchain technologies work. You can get more information here:

There are various tools out there that can help you get the information about crypto as fast as possible. However, the tool recommended for analyzing cryptocurrency articles is Diffbot.

Diffbot — a developer tool that aims to crawl the whole internet, analyze the data, and create the biggest knowledge graph in the world — can give application programming interface (API) endpoints that can retrieve anything about crypto. To do so, you’ll also need Neo4j and knowledge in coding.


The solution with Diffbot has six steps:

First, as previously mentioned, Diffbot has API endpoints on their Knowledge Graph (KG). Using these, you can retrieve articles, as well as information on organizations, persons, and such. With the right code, you can pull several relevant cryptocurrency articles.

You may find that some of the retrieved articles you see will be in different foreign languages since they’ll be pulled from around the world. As such, you can use Google Translate API to translate them into English. To get this done you will need to create an API key. It is also important to check the pricing. As some can be too expensive. For you not to be caught on aware, it’s good to check the price. In my search, we found that the pricing should be between $15 to $20 to translate a million characters. The next importing the articles to Neo4j

Afterward, import the articles into Neo4j, where you can make graph data models to visualize data. To import the articles successfully for analysis, you will need to either download the Neo4j desktop or use the free Neo4j AuraDB cloud instance. This tool is enough to store up to 5000 articles. As I earlier mentioned you will need to import certain codes which will be run and you get to see certain schema. Which are gotten from the articles. This makes pattern detection and data analysis easier. When the coding is done right, you get to see some metadata around articles.


When you’re done importing the data, you can now extract “facts” (which are essentially entities and relationships) using Diffbot’s NLP API. Here, when you input any text, the API will identify all keywords and phrases related to it and possible relationships between them. You also get to know who write these articles and which website these articles were posted on. In addition, the Diffbot API also returns the categories to which each article belongs. Here you get to examine a single blog post and verify the graph schema model. The Diffbot site offers an online NLP demo where you are free to input any text and evaluate the results. The NLP API recognizes all the entities that appear in the text and the possible relationship that exit between them. It also makes the results clearer by showing them on a graph. The Diffbot API also has another entity linking feature. These features help link entities to Wikipedia, Crunchbase, or LinkedIn.

Next, you’ll clean and import those relationships into Neo4j. After that, process those articles by sending multiple of them in a single request. When you finish this point, you’ll have created a KG in Neo4j.

Finally, you’ll be analyzing the graph — and there are many options. For one, you can evaluate which keywords and phrases appear most often in the articles in a given timeline. Another thing you can do is look at the sentiment about a certain topic, say bitcoin, and group it by region. With this, you’ll see which areas look at bitcoin positively, and which negatively. However, these sentiments heavily fluctuate between articles based on the standard deviation figures.


Using Diffbot can make the process of monitoring the cryptocurrency space easier thanks to its APIs that can quickly pull any information you need. As we earlier mentioned, you could monitor news and information regarding your company and the whole industry. This information may help you try to predict future events. You can also use the extracted data to improve your machine learning skill.

About Lana Evanom

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