Multiagent-based Youtube Content Discovery Bot-Reference-Cited by-同舟云学术

Multiagent-based Youtube Content Discovery Bot

Published:2023-11-06 Issue: Volume: Page:450-453
ISSN:
Container-title:Proceedings of the International Conference on Advances in Social Networks Analysis and Mining
language:
Short-container-title:

Author:

Solaiman Ishmam Ahmed¹^ORCID,Agarwal Nitin²^ORCID

Affiliation:

1. Computer Science, University of Arkansas at Little Rock, Little Rock, Arkansas, United States

2. Information Science / COSMOS, University of Arkansas at Little Rock, Little Rock, Arkansas, United States

Funder

U.S. National Science Foundation

U.S. Office of the Under Secretary of Defense for Research and Engineering

U.S. Office of Naval Research

U.S. Air Force Research Laboratory, U.S. Army Research Office

U.S. Defense Advanced Research Projects Agency

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3625007.3627501

Reference11 articles.

1. Alexa. (n.d.). YouTube.com traffic demographics and competitors. Retrieved from https://www.alexa.com/siteinfo/youtube.com

2. Network analysis of Youtube videos based on keyword search with graph centrality approach

3. Kready, J., Hussain, M. N., & Agarwal, N. (2020, May 22). YouTube data collection using parallel processing. Paper presented at the IEEE Workshop on Parallel and Distributed Processing for Computational Social Systems (ParSocial 2020), New Orleans, Louisiana, USA.

4. Cakmak M. Okeke O. Spann B. & Agarwal N. (2023 May 15--19). Adopting parallel processing for rapid generation of transcripts in multimedia-rich online information environment. Paper presented at the 7th IEEE Workshop on Parallel and Distributed Processing for Computational Social Systems (ParSocial 2023) co-located with the 37th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2023) St. Petersburg Florida USA.

5. Oberlo. (n.d.). 10 YouTube stats every marketer should know in 2023 [Infographic]. Retrieved from https://www.oberlo.com/blog/youtube-statistics