Examining Video Recommendation Bias on YouTube
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-78818-6_10
Reference24 articles.
1. Abdollahpouri, H., Burke, R., Mobasher, B.: Controlling popularity bias in learning-to-rank recommendation. In: Proceedings of the Eleventh ACM Conference on Recommender Systems (RecSys 2017), pp 42–46 (2020)
2. Alstott, J., Bullmore, E., Plenz, D.: Power-law: a Python package for analysis of heavy-tailed distributions. PloS One 9(1), e85777 (2014)
3. Bellogín, A., Castells, P., Cantador, I.: Statistical biases in information retrieval metrics for recommender systems. Inf. Retriev. J. 20(6), 606–634 (2017). https://doi.org/10.1007/s10791-017-9312-z
4. Beutel, A., et al.: Fairness in recommendation ranking through pairwise comparisons. In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2019), pp. 2212–2220 (2019)
5. Boratto, L., Marras, M., Faralli, S., and Stilo, G.: International workshop on algorithmic bias in search and recommendation (Bias 2020). In: Jose, J. et al. (eds.) Advances in Information Retrieval. ECIR 2020. Lecture Notes in Computer Science. Springer (2020)
Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. The bias beneath: analyzing drift in YouTube’s algorithmic recommendations;Social Network Analysis and Mining;2024-08-24
2. Introduction: hyper-visuality: images in the era of social platforms, digital archives and computational economies;Visual Communication;2024-08
3. Investigating Consumers’ Purchase Resistance Behavior to AI-Based Content Recommendations on Short-Video Platforms: A Study of Greedy And Biased Recommendations;Journal of Internet Commerce;2024-07-02
4. Authoring a TopHat E-Book from Existing Videos: An Explanation and Results from Two Years of Flipping an Organic Chemistry Course;Journal of Chemical Education;2024-05-30
5. Beyond the Trends: Evolution and Future Directions in Music Recommender Systems Research;IEEE Access;2024
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3