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Welcome, I'm your host Jess Wisse. On today's episode we'll be unveiling new research coming out of PNNL’s Data Sciences and Analytics Group, but before we unpack that here's a bit more information from our co-host Jessica Bernsen.

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Jessica Bernsen: Humans are social animals. Nowhere is that more apparent in today's modern world than on social media. Log in to your favorite social media platforms and you'll find a slew of conversations, debates, news, and more. PNNL researchers took all of this data and built a quantitative framework to better understand communication patterns and how information spreads online.

Meet Svitlana.

Svitlana Volkova: My name is Svitlana Volkova and I am a senior scientist at PNNL. I've been here for three years, and my work involves machine learning, deep learning, natural language processing, and computational social science. I work a lot with social data.

Jess Wisse: Findings gathered by Svitlana and her colleagues Maria Glensky and Emily Saldana shed led light on to how cryptocurrency discussions spread and they also could inform artificial intelligence applications used to forecast things like cryptocurrency prices.

Svitlana Volkova: So in this paper we analyzed almost three years worth of data; a lot of discussions, millions of posts, and comments and that’s what makes this research interesting that like we have access to this vast amount of data that we have the techniques and methodology to analyze really fast and draw some insights and scientific conclusions from this data that can in turn inform machine learning and deep learning models to predict the future.

Jessica Bernsen: Nobody really looked into how information about cryptocurrency spreads on reddit specifically and that's what Svitlana and her team did.

Svitlana Volkova: The current data set included the historical rise of the Bitcoin price and we specifically

wanted to look into social signals around this historical event when the price is increasing and then decreasing we wanted to see how social environments are reflecting this change.

We found that across of three coins, the discussion spread is very different.

We know that Bitcoin is the most popular coin, and that was reflected in our analysis.

We found that comments on a Bitcoin post about was the fastest—on average people responded in 11 minutes to discussions about Bitcoin versus Monero and Ethereum.

In Ethereum threads, it takes people at least 30 minutes to follow up on a on a post, but interestingly we found that Monero has really long, ongoing conversations compared to Bitcoin conversations that have a very short life time.

They don’t live long.

And Bitcoin conversation focus on a specific audience, which on average is between 2 and 6 people. Monero conversations involve more people, and more diverse audiences. And structurally the discussions are very different.

The Monero discussions are like chains. They go deep. And at each level they have a specific size of the audience. Bitcoin discussions are more diverse, and they form trees, and they go more viral compared to Monero.

Jess Wisse: Svitlana and her team looked in to reddit, but their research can also be applied to a variety of platforms. For example, the framework they designed for measuring information spread can be also be extended to measure the spread of other types of information. Such as images on Instagram, videos on YouTube, hashtags on Twitter.

Svitlana Volkova: This analysis would be very helpful for a different predictive analytics so for example you can look how discussions spread around different cryptocu