{"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/lancaster-a-at-semeval-2017-task-5-evaluation","title":"Lancaster A at SemEval-2017 Task 5: Evaluation metrics matter: predicting sentiment from financial news headlines","arxiv_id":"1705.00571","date":"2017-05-01","proceeding":"SEMEVAL 2017 8","authors":["Andrew Moore","Paul Rayson"],"abstract":"This paper describes our participation in Task 5 track 2 of SemEval 2017 to\npredict the sentiment of financial news headlines for a specific company on a\ncontinuous scale between -1 and 1. We tackled the problem using a number of\napproaches, utilising a Support Vector Regression (SVR) and a Bidirectional\nLong Short-Term Memory (BLSTM). We found an improvement of 4-6% using the LSTM\nmodel over the SVR and came fourth in the track. We report a number of\ndifferent evaluations using a finance specific word embedding model and reflect\non the effects of using different evaluation metrics.","url_abs":"http://arxiv.org/abs/1705.00571v1","url_pdf":"http://arxiv.org/pdf/1705.00571v1.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":"lancaster-a-at-semeval-2017-task-5-evaluation","repo_url":"https://github.com/apmoore1/semeval","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"regression-1","task_name":"regression"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1705.00571","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}