{"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/nilc-usp-at-semeval-2017-task-4-a-multi-view","title":"NILC-USP at SemEval-2017 Task 4: A Multi-view Ensemble for Twitter Sentiment Analysis","arxiv_id":"1704.02263","date":"2017-04-07","proceeding":"SEMEVAL 2017 8","authors":["Edilson A. Corrêa Jr.","Vanessa Queiroz Marinho","Leandro Borges dos Santos"],"abstract":"This paper describes our multi-view ensemble approach to SemEval-2017 Task 4\non Sentiment Analysis in Twitter, specifically, the Message Polarity\nClassification subtask for English (subtask A). Our system is a voting\nensemble, where each base classifier is trained in a different feature space.\nThe first space is a bag-of-words model and has a Linear SVM as base\nclassifier. The second and third spaces are two different strategies of\ncombining word embeddings to represent sentences and use a Linear SVM and a\nLogistic Regressor as base classifiers. The proposed system was ranked 18th out\nof 38 systems considering F1 score and 20th considering recall.","url_abs":"http://arxiv.org/abs/1704.02263v1","url_pdf":"http://arxiv.org/pdf/1704.02263v1.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":"nilc-usp-at-semeval-2017-task-4-a-multi-view","repo_url":"https://github.com/edilsonacjr/semeval2017","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"sentiment-analysis","task_name":"Sentiment Analysis"},{"task_slug":"twitter-sentiment-analysis","task_name":"Twitter Sentiment Analysis"},{"task_slug":"word-embeddings","task_name":"Word Embeddings"}],"methods":[{"method_slug":"svm","method_name":"SVM"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}