Cryptocurrency enthusiasts already know how valuable the blockchain and digital currencies are, and the role that they play in society. However, crypto is also being shown to have additional value in ways many have not considered. Computer scientists are using crypto-related threads on Reddit in order to study the propagation of disinformation across the internet.
Computer Scientists at the Pacific Northwest National Laboratory (PNNL), a lab operated in Washington State by the U.S. Department of Energy, have reportedly dug deep into Reddit discussions to map the ebb and flow of crypto chatter. The goal is to see how online discussions can predict responses in the market, as well as to understand how disinformation goes viral.
According to one of PNNL’s data scientists, Svitlana Volkova, “Cryptocurrency is a very good proxy program for disinformation.” Volkova is one of the authors of the study, which was presented at the Web Conference 2019 held in San Francisco.
The cycles of crypto prices have occupied the news wires for the past several years, as have campaigns designed to spread disinformation, such as what was seen during the U.S. presidential elections in 2016. That same activity is expected to surface ahead of the 2020 elections, but could be even more widespread. As a result, scientists want to determine how to target the false information and keep it from becoming viral.
The PNNL scientists conducted tests to see how quickly crypto discussions on Reddit took off, how many participated in the threads, how engagement was facilitated and how the threads were generated. Analyzing the results, certain patterns began to emerge.
SegWitCoin (BTC) produced the most activity—3,600 comments each day on average. Ethereum (ETH) and Monero (XMR) only had 500 and 380, respectively. In general, responses to BTC posts were twice as fast as those for the other currencies, as well. ETH discussions had the largest possible lifetime, but discussions about XMR, which has been more closely tied to illegal transactions, had the largest median lifetimes.
Volkova states in a news release, “These social signals are quite useful, and by incorporating them with machine and deep learning, we intend to build predictive models that hit on causal relationships between different variables so we can explain model decision-making processes.”
The researchers aren’t done yet, though. Another study is planned that is based on a system designed to extract social signals from social media posts and correlate them to crypto prices. A separate project will be conducted by the group to track pump-and-dump investment schemes on Telegram.
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