DyEmo: Danmu captures temporal and state-space structure in population-level emotion dynamics

Shen Xinke, Li Zongsheng, Zhong Jiani, Chen Xuyang, Lou Kexin, Wang Song, Su Shiyue, Peng Kaining, Xu Xin, Wu Haiyan, Wang Dong, Zhang Dan, Liu Quanying

Open source

DOI: 10.57760/sciencedb.32696
Published: 2026
Container: Not recorded
Publisher: Science Data Bank
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.57760/sciencedb.32696,
  title = {DyEmo: Danmu captures temporal and state-space structure in population-level emotion dynamics},
  author = {Shen Xinke and Li Zongsheng and Zhong Jiani and Chen Xuyang and Lou Kexin and Wang Song and Su Shiyue and Peng Kaining and Xu Xin and Wu Haiyan and Wang Dong and Zhang Dan and Liu Quanying},
  year = {2026},
  doi = {10.57760/sciencedb.32696},
  url = {https://doi.org/10.57760/sciencedb.32696}
}

RIS

TY  - JOUR
TI  - DyEmo: Danmu captures temporal and state-space structure in population-level emotion dynamics
AU  - Shen Xinke
AU  - Li Zongsheng
AU  - Zhong Jiani
AU  - Chen Xuyang
AU  - Lou Kexin
AU  - Wang Song
AU  - Su Shiyue
AU  - Peng Kaining
AU  - Xu Xin
AU  - Wu Haiyan
AU  - Wang Dong
AU  - Zhang Dan
AU  - Liu Quanying
PY  - 2026
DO  - 10.57760/sciencedb.32696
UR  - https://doi.org/10.57760/sciencedb.32696
ER  -

APA

Xinke, S., Zongsheng, L., Jiani, Z., Xuyang, C., Kexin, L., Song, W., Shiyue, S., Kaining, P., Xin, X., Haiyan, W., Dong, W., Dan, Z., & Quanying, L. (2026). DyEmo: Danmu captures temporal and state-space structure in population-level emotion dynamics. https://doi.org/10.57760/sciencedb.32696

Source records

datacite · retrieved 2026-09-25T04:00:25.711Z