Our commitment to advancing knowledge and literacy of the blockchain and cryptocurrency market is demonstrated through our efforts to expand the available resources for this rapidly growing industry. This is achieved by developing and releasing a variety of datasets and tools that can be used by researchers, academics, analysts, and professionals in the field. We aim to provide accurate and up-to-date information to help further the understanding of blockchain and cryptocurrency and support its continued growth and development.

Who can benefit?

Apart from members of our University Network, who will benefit from accessing a freemium model, a wide range of individuals and groups within the blockchain and cryptocurrency market can benefit including:

Independent Researchers - who can use the tools and datasets to conduct academic research and contribute to the advancement of knowledge in the field.
Academics - who can incorporate the resources into their teaching materials to provide students with up-to-date information and practical examples.
Developers - who can build on top of our resources and use our tools to explore new directions.
Blockchain community managers - who can better monitor their community performance through our indicators.
Analysts - who can use the datasets to analyse market trends and make informed predictions about the future of blockchain and cryptocurrency.
Professionals in the field - who can utilize the tools and datasets to inform their work and make informed decisions about their investments or business strategies.
Industry CIO - who can access to accurate information and sources can help stay informed about the latest developments and make informed decisions.
Auditors - who can use our instruments to promote transparency and to identify and mitigate financial risks and provide guidance on regulatory compliance. 
Crypto Regulators - who can better understand a project's critical limits and risks.

We aggregate information from public online communities across instant messaging, microblogging and social network platforms. Hundreds of millions of records are retrieved and run through several GDPR-compliant data cleaning, anonymisation and verification algorithms to ensure data integrity before being organised and analysed.

We harness this massive amount of unstructured data and provide accurate, timely and unbiased analytics of social media content using proprietary algorithms and methodologies in the area of data mining and artificial intelligence including machine learning neural networks and deep learning.

The analysis is synthetised in proprietary indexes capturing unique social media dynamics.

These tools currently include datasets with daily data from platforms such as Telegram and Reddit, but an upcoming version will include also Twitter, Stocktwits, Yahoo Finance, Github, Coinmarketcap chat and BitcoinTalk.

Tools Available from Q2 2023

Trust index

The Trust Index is an unbiased synthetic indicator which summarises the overall fairness and quality of chat group and forum discussions. The Trust Index is obtained aggregating several other sub-indexes calculated by taking into the equation the statistical and network properties of the following quantitative measures: Users activity; Messages; Bots; Sensitive words; association to other low quality chat groups; chat administrator and moderator performance. Some, but not all, of the main quantitative dimensions represented can be connected to the engagement of the chat group participants, the responsiveness of the administrators, the reliability of the users involved, the quality of the content generated and the soundness of the idiom used

Mood index

The Mood Index provides sentiment-driven cryptocurrency signals. We built a proprietary sentiment dictionary to estimate sentiment across tens of thousands of open chats and forum in the crypto space. We identify emotional properties embodied in the messages together with a measure of the confidence in our estimates.

Tools Available from Q2 2023

Scam index

The Scam Index is a proprietary unbiased measure of the level of scams and swindles in online social media communities. We use proprietary metrics and Machine Learning algorithms to develop online fraud forensics and detect phishing scams, impersonations - fake accounts, worms, bot spams, money-based schemes and Ponzi schemes.

Spam index

The Spam Index measures the level of spamming activities in online social media forums and chat groups. We use proprietary metrics and Deep Learning algorithms and Computer Visions techniques to detect irrelevant or unsolicited messages in online forums and chats group discussions.

Emerging digital technologies like DLT have the potential to drive positive change in a wide range of Environmental, Social, and Governance (ESG) issues. However, the energy consumption required by some blockchain networks has raised concerns about their carbon footprint and impact on the environment. As such, tracking and ranking blockchains based on their carbon footprint can help to incentivise more sustainable practices and promote the adoption of greener alternatives, making DLT an even more powerful force for positive change in the future.

In the spirit of the DSFs commitment to maximising DLT’s positive impact, to share knowledge and to foster the open and transparent development of digital ledger ecosystems we have developed proprietary tools measuring:  

  • Quantitative (raw and pre-processed) data points on crypto global energy consumption 
  • Energy consumption per transaction
  • Carbon footprint
  • ESG sustainability and transparency metrics. 

On-chain analytics tools

The DLT Science Foundation is developing advanced on-chain data analytics tools that will provide invaluable real-world insights into DLTs. This powerful tool will offer deep insights into ledger phenomena, including:

  • PoS chain staking dynamics,
  • DeFi behavioural analysis,
  • transaction network graph analysis,
  • and more.

This will provide perspectives on network health and profitability, market trends, user sentiment, and risk management. Metrics such as validator performance and rewards distribution will enable stakeholders to better understand network status and even inform resource allocation decisions. Additionally, the tools will give users a detailed comprehension of the flow of value within blockchain networks, helping them identify key players and trends.

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