{"title":"用情感分析调查大型公共部门项目的失败","authors":"S. Purao, K. Desouza, Jonathan Becker","doi":"10.2979/ESERVICEJ.8.2.84","DOIUrl":null,"url":null,"abstract":"We describe results from historical analysis of the IRS Business Systems Modernization (BSM) as an example of large-scale, public sector projects. The project has already spanned a decade and consumed more than 3 billion dollars. The paper suggests extracting stakeholder Sentiments and Confidence from documents, with a view to exploring how such measures may offer early indications of project progress and assist managers to prevent undesirable future outcomes. The key contribution of this research is a demonstration of a plausible technique to elicit stakeholder perspectives based on the content in publicly available documents, either complementing any existing methods, or supplanting them in projects where collecting primary data may be infeasible.","PeriodicalId":133558,"journal":{"name":"e-Service Journal","volume":"116 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Investigating Failures in Large-Scale Public Sector Projects with Sentiment Analysis\",\"authors\":\"S. Purao, K. Desouza, Jonathan Becker\",\"doi\":\"10.2979/ESERVICEJ.8.2.84\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We describe results from historical analysis of the IRS Business Systems Modernization (BSM) as an example of large-scale, public sector projects. The project has already spanned a decade and consumed more than 3 billion dollars. The paper suggests extracting stakeholder Sentiments and Confidence from documents, with a view to exploring how such measures may offer early indications of project progress and assist managers to prevent undesirable future outcomes. The key contribution of this research is a demonstration of a plausible technique to elicit stakeholder perspectives based on the content in publicly available documents, either complementing any existing methods, or supplanting them in projects where collecting primary data may be infeasible.\",\"PeriodicalId\":133558,\"journal\":{\"name\":\"e-Service Journal\",\"volume\":\"116 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"e-Service Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2979/ESERVICEJ.8.2.84\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"e-Service Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2979/ESERVICEJ.8.2.84","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Investigating Failures in Large-Scale Public Sector Projects with Sentiment Analysis
We describe results from historical analysis of the IRS Business Systems Modernization (BSM) as an example of large-scale, public sector projects. The project has already spanned a decade and consumed more than 3 billion dollars. The paper suggests extracting stakeholder Sentiments and Confidence from documents, with a view to exploring how such measures may offer early indications of project progress and assist managers to prevent undesirable future outcomes. The key contribution of this research is a demonstration of a plausible technique to elicit stakeholder perspectives based on the content in publicly available documents, either complementing any existing methods, or supplanting them in projects where collecting primary data may be infeasible.