
We further provide two supplementary files that enrich the KuaiRand dataset with video-level content-side semantic information. These files can be seamlessly joined with the main dataset via the shared key final_video_id. A detailed description of these supplementary files is provided here If you find this dataset useful in your research, we kindly ask that you cite the following paper: @inproceedings{gao2022kuairand, title = {KuaiRand: An Unbiased Sequential Recommendation Dataset with Randomly Exposed Videos}, author = {Gao, Chongming and Li, Shijun and Zhang, Yuan and Chen, Jiawei and Li, Biao and Lei, Wenqiang and Jiang, Peng and He, Xiangnan}, url = {https://doi.org/10.1145/3511808.3557624}, doi = {10.1145/3511808.3557624}, booktitle = {Proceedings of the 31st ACM International Conference on Information and Knowledge Management}, series = {CIKM '22}, location = {Atlanta, GA, USA}, numpages = {5}, year = {2022}, pages = {3953–3957} }
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
