China 
Africa 
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How Information Technology Is Changing E-business on the Way to the Digital Economy
Published in Anna Brzozowska, Dagmara Bubel, Larysa Nekrasenko, Organisation Management in the Digital Economy, 2022
Anna Brzozowska, Dagmara Bubel, Larysa Nekrasenko
The list of cryptocurrencies can be divided into five parts:Recognised cryptocurrencyCryptocurrency with a large market shareAlternative cryptocurrencies (mainly Forks)Forkom (with minimal modifications)Clones. They have no prospects. They differ from the fork in the absence of innovations.The most popular cryptocurrencies in the world in 2021 were:Bitcoin (BTC)Ethereum (ETH)Solana (SOL)Cardano (ADA)Dogecoin (DOGE)Yearn.finance (YFI)Polygon (MATIC)Unfortunately, now there are more and more speculative cryptocurrencies. This is because only a few dozen people possess 80% of cryptocurrencies.
Bi-Directional CNN-RNN Architecture with Group-Wise Enhancement and Attention Mechanisms for Cryptocurrency Sentiment Analysis
Published in Applied Artificial Intelligence, 2022
Gül Cihan Habek, Mansur Alp Toçoğlu, Aytuğ Onan
In this paper, we collected a raw dataset consists of 25,000 Turkish cryptocurrency-related tweets by using a social networking service scraper named SNScrape library. The tweets are gathered from April 20, 2021 to March 20, 2022. To do so, we fetched the tweets which are tagged to fourteen specific hashtags which are #avax, #avalanche, #bitci, #btc, #bitcoin, #chz, #chiliz, #eth, #ethereum, #solana, #xrp, #crypto, #nft, #defi. In the annotation process of the raw data, each tweet is labeled as positive, negative, neutral and not crypto-related by two annotators. After the annotation process, the size of the dataset declined to 9,548 tweets in total because we eliminated the tweets categorized as neutral and not crypto-related and the tweets which are no consensus on the labeling results of the annotators. As a result, 5,907 tweets are labeled as positive and the rest 3,641 tweets are labeled as negative. Next, we preprocessed the dataset for empirical research. Firstly, we removed tags, usernames and links, which are ineffective and meaningless data for training machine learning models, from each tweet. After that, we converted all letters to lowercase and eliminated numeric characters, extra spaces, and punctuation marks. In the next step, we performed Porter stemmer to normalize the dataset (Pedregosa et al. 2011). Lastly, a pre-defined NLTK Turkish stopword list was used to extract stopwords in the dataset. In addition, we assessed the predictive performance of the proposed architecture on a well-known sentiment classification benchmark (i.e., Sentiment140 dataset) in this study. It contains 1,600,000 tweets that have been automatically classified as positive or negative (Go, Bhayani, and Huang 2009).
A study on Diem and Aptos distributed ledger technology
Published in International Journal of Parallel, Emergent and Distributed Systems, 2023
Giuseppe Antonio Pierro, Giacomo Ibba, Roberto Tonelli
A transaction in the account-based model triggers nodes to decrement the balance of the sender's account and increment the balance of the receiver's account [36]. The Ethereum [25] and Solana [37] blockchain uses the account-based model.