{"title":"在博客中识别从业者的论点和证据:来自一项试点研究的见解","authors":"A. Williams, A. Rainer","doi":"10.1109/APSEC.2016.056","DOIUrl":null,"url":null,"abstract":"Background: researchers have a limited understanding of how practitioners conceive of and use evidence. Objective: to investigate how to automatically identify practitioner arguments and evidence in a corpus of practitioner documents, and identify insights for further work. Method: we develop, apply and evaluate a preliminary process to identify practitioner arguments and factual stories, based on the presence of specific words, using a sample of 1,022 blog posts from a software practitioner's blog. Results: we identify unanswered questions relating to the process: selecting and scraping data, cleansing data, parsing components of arguments and stories, selecting the 'right' cases, and validating and interpreting the results. Conclusion: our work provides a foundation for more substantive research on identifying practitioners' evidence and arguments that, in turn, can support research in other areas e.g. evidence informed software practice.","PeriodicalId":339123,"journal":{"name":"2016 23rd Asia-Pacific Software Engineering Conference (APSEC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Identifying Practitioners' Arguments and Evidence in Blogs: Insights from a Pilot Study\",\"authors\":\"A. Williams, A. Rainer\",\"doi\":\"10.1109/APSEC.2016.056\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: researchers have a limited understanding of how practitioners conceive of and use evidence. Objective: to investigate how to automatically identify practitioner arguments and evidence in a corpus of practitioner documents, and identify insights for further work. Method: we develop, apply and evaluate a preliminary process to identify practitioner arguments and factual stories, based on the presence of specific words, using a sample of 1,022 blog posts from a software practitioner's blog. Results: we identify unanswered questions relating to the process: selecting and scraping data, cleansing data, parsing components of arguments and stories, selecting the 'right' cases, and validating and interpreting the results. Conclusion: our work provides a foundation for more substantive research on identifying practitioners' evidence and arguments that, in turn, can support research in other areas e.g. evidence informed software practice.\",\"PeriodicalId\":339123,\"journal\":{\"name\":\"2016 23rd Asia-Pacific Software Engineering Conference (APSEC)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 23rd Asia-Pacific Software Engineering Conference (APSEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APSEC.2016.056\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 23rd Asia-Pacific Software Engineering Conference (APSEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APSEC.2016.056","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identifying Practitioners' Arguments and Evidence in Blogs: Insights from a Pilot Study
Background: researchers have a limited understanding of how practitioners conceive of and use evidence. Objective: to investigate how to automatically identify practitioner arguments and evidence in a corpus of practitioner documents, and identify insights for further work. Method: we develop, apply and evaluate a preliminary process to identify practitioner arguments and factual stories, based on the presence of specific words, using a sample of 1,022 blog posts from a software practitioner's blog. Results: we identify unanswered questions relating to the process: selecting and scraping data, cleansing data, parsing components of arguments and stories, selecting the 'right' cases, and validating and interpreting the results. Conclusion: our work provides a foundation for more substantive research on identifying practitioners' evidence and arguments that, in turn, can support research in other areas e.g. evidence informed software practice.