[Objective] The paper proposes a tripartite network sentiment analysis method, aiming to reflect the indirect connections between nodes. [Methods] We constructed a “user-product-sentiment tag” tripartite network, which were split into three bipartite networks for network structure analysis. Then, we used the proposed tripartite network projection method to obtain the “two-sentiment one-mode” network of users and products. [Results] We obtained the association of high-weighted related nodes from NetEase Cloud music dataset, and information such as genre classifications, hot-rated songs, and fan groups. [Limitations] The large number of user nodes need to be visualized in the future. [Conclusions] Based on the formation, splitting and projection of the sentiment tripartite network, we present the indirect connection between nodes, and provide new perspectives for network sentiment analysis. © 2019 The Author(s).
