{"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/content-based-popularity-prediction-of-online","title":"Content-based Popularity Prediction of Online Petitions Using a Deep Regression Model","arxiv_id":"1805.06566","date":"2018-05-17","proceeding":"ACL 2018 7","authors":["Shivashankar Subramanian","Timothy Baldwin","Trevor Cohn"],"abstract":"Online petitions are a cost-effective way for citizens to collectively engage\nwith policy-makers in a democracy. Predicting the popularity of a petition ---\ncommonly measured by its signature count --- based on its textual content has\nutility for policy-makers as well as those posting the petition. In this work,\nwe model this task using CNN regression with an auxiliary ordinal regression\nobjective. We demonstrate the effectiveness of our proposed approach using UK\nand US government petition datasets.","url_abs":"http://arxiv.org/abs/1805.06566v1","url_pdf":"http://arxiv.org/pdf/1805.06566v1.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":"content-based-popularity-prediction-of-online","repo_url":"https://github.com/shivashankarrs/Petitions","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"regression-1","task_name":"regression"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}