Tabassum Sultana, Eric R. Harley, Gavin Adamson, Asmaa Malik
{"title":"Extracting Source Information From News Articles: Information Extraction","authors":"Tabassum Sultana, Eric R. Harley, Gavin Adamson, Asmaa Malik","doi":"10.1145/3582768.3582774","DOIUrl":null,"url":null,"abstract":"One of the factors influencing the credibility of news is source attribution. Ideally, news would be based on a balanced variety of sources. In this work we use spaCy1 and Python2 to identify sources of information cited in news articles and assign the sources to categories, as a first step in building software that assesses the balance and breadth of the sourcing in news articles. The preliminary testing of the software indicates that identification of the sources has a recall of 73% and accuracy of 95%, and the sources are categorized with overall accuracy of 78%.","PeriodicalId":315721,"journal":{"name":"Proceedings of the 2022 6th International Conference on Natural Language Processing and Information Retrieval","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2022 6th International Conference on Natural Language Processing and Information Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3582768.3582774","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
One of the factors influencing the credibility of news is source attribution. Ideally, news would be based on a balanced variety of sources. In this work we use spaCy1 and Python2 to identify sources of information cited in news articles and assign the sources to categories, as a first step in building software that assesses the balance and breadth of the sourcing in news articles. The preliminary testing of the software indicates that identification of the sources has a recall of 73% and accuracy of 95%, and the sources are categorized with overall accuracy of 78%.