{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/redqueen-an-online-algorithm-for-smart","title":"RedQueen: An Online Algorithm for Smart Broadcasting in Social Networks","arxiv_id":"1610.05773","date":"2016-10-18","proceeding":null,"authors":["Ali Zarezade","Utkarsh Upadhyay","Hamid Rabiee","Manuel Gomez Rodriguez"],"abstract":"Users in social networks whose posts stay at the top of their followers'{}\nfeeds the longest time are more likely to be noticed. Can we design an online\nalgorithm to help them decide when to post to stay at the top? In this paper,\nwe address this question as a novel optimal control problem for jump stochastic\ndifferential equations. For a wide variety of feed dynamics, we show that the\noptimal broadcasting intensity for any user is surprisingly simple -- it is\ngiven by the position of her most recent post on each of her follower's feeds.\nAs a consequence, we are able to develop a simple and highly efficient online\nalgorithm, RedQueen, to sample the optimal times for the user to post.\nExperiments on both synthetic and real data gathered from Twitter show that our\nalgorithm is able to consistently make a user's posts more visible over time,\nis robust to volume changes on her followers' feeds, and significantly\noutperforms the state of the art.","url_abs":"http://arxiv.org/abs/1610.05773v1","url_pdf":"http://arxiv.org/pdf/1610.05773v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"redqueen-an-online-algorithm-for-smart","repo_url":"https://github.com/Networks-Learning/RedQueen","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}