  Cryptoassets are growing rapidly worldwide. One of the large cap cryptoassets
is XRP. In this article, we focus on analyzing transaction data for the
2017-2018 period that consist one of the significant XRP market price bursts.
We construct weekly weighted directed networks of XRP transactions. These
weekly networks are embedded on continuous vector space using a network
embedding technique that encodes structural regularities present in the network
structure in terms of node vectors. Using a suitable time window we calculate a
correlation tensor. A double singular value decomposition of the correlation
tensor provides key insights about the system. The significance of the
correlation tensor is captured using a randomized correlation tensor. We
present a detailed dependence of correlation tensor on model parameters.
