Research on quality evaluation of user generated content in new media academic community

Chaonan Jin; Junjie Gong

doi:10.1117/12.2671445

28 April 2023 Research on quality evaluation of user generated content in new media academic community

Chaonan Jin, Junjie Gong

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 126101A (2023) https://doi.org/10.1117/12.2671445
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

With the rapid development of digital technology and the popularization of terminal equipment, the new media academic community is booming. The knowledge information in the academic community is mainly generated by the user 's posting and replying, so the quality of academic resources is closely related to the creator 's knowledge level and cultural background. However, the user level is mixed and difficult to evaluate, which makes the academic community user generated content have high redundancy and low quality, and seriously reduces the efficiency of academic users to acquire knowledge. Therefore, this paper uses Word2Vec word embedding model and professional domain dictionary to vectorize and automatically label user-generated content, and then trains the Bi-GRU neural network model to construct the quality evaluation method of user-generated content, which provides a basis for the quality identification and evaluation of user generated content in the new media academic community.

Citation Download Citation

Chaonan Jin and Junjie Gong "Research on quality evaluation of user generated content in new media academic community", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 126101A (28 April 2023); https://doi.org/10.1117/12.2671445

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