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One-class graph moderating attention neural network in quality assessment of creative ideas

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Abstract

The identification and implementation of high-quality ideas have been hindered in the open innovation community due to information overload. Most existing studies tended to utilize the factors that influence the quality of ideas to construct the methods to assess the quality of ideas, which ignores the deeper information contained in the community system environment where the creative idea is located. This paper regards a community as a complex social system formed by user sharing and interaction from a systemic perspective. A one-class graph moderating attention neural network model (OCGMAT) is constructed to map this social network system and mine the in-depth information of the system’s impact on ideas quality, especially the moderating effect of interactive emotion. The OCGMAT model includes five layers, a mapping layer to map the network information of the social system to graph-structured data, a multi-head moderating attention layer to calculate the attention coefficient between the two neighboring nodes under the moderating effect of interactive emotion, two convolutional layers to extract the deep representation of features, a fully connected layer to classify the quality of creative ideas. The experiments for OCGMAT, GAT, GNN, and other classification-based models have been conducted on the creative ideas dataset from the Meizu open innovation community, which shows that the OCGMAT model outperforms other methods with high accuracy of 93.22%. Finally, according to the predictions, we take measures to manage creative ideas and improve innovation effectiveness.

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Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Code availability

The code that supports the findings of this study is available from the corresponding author upon reasonable request.

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  1. School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing, China

    Yang Yang

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Yang, Y. One-class graph moderating attention neural network in quality assessment of creative ideas. Neural Comput & Applic 36, 3369–3388 (2024). https://doi.org/10.1007/s00521-023-09256-8

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