{"title":"On the Validity of Using Webpage Texts to Identify the Target Population of a Survey: An Application to Detect Online Platforms","authors":"Piet Daas, Wolter Hassink, Bart Klijs","doi":"10.1177/0282423x241235265","DOIUrl":null,"url":null,"abstract":"A statistical classification model was developed to identify online platform organizations based on the texts on their website. The model was subsequently used to identify all (potential) platform organizations with a website included in the Dutch Business Register. The empirical outcomes of the statistical model were plausible in terms of the words and the bimodal distribution of fitted probabilities, but the results indicated an overestimation of the number of platform organizations. Next, the external validity of the outcomes was investigated through a survey of the organizations that were identified as a platform organization by the statistical classification model. The response by the organizations to the survey confirmed a substantial number of type-I errors. Furthermore, it revealed a positive association between the fitted probability of the text-based classification model and the organization’s response to the survey question on being an online platform organization. The survey results indicated that the text-based classification model can be used to obtain a subpopulation of potential platform organizations from the entire population of businesses with a website. This subpopulation may form a good starting point to study platform organizations in more detail.","PeriodicalId":51092,"journal":{"name":"Journal of Official Statistics","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Official Statistics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1177/0282423x241235265","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"SOCIAL SCIENCES, MATHEMATICAL METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
A statistical classification model was developed to identify online platform organizations based on the texts on their website. The model was subsequently used to identify all (potential) platform organizations with a website included in the Dutch Business Register. The empirical outcomes of the statistical model were plausible in terms of the words and the bimodal distribution of fitted probabilities, but the results indicated an overestimation of the number of platform organizations. Next, the external validity of the outcomes was investigated through a survey of the organizations that were identified as a platform organization by the statistical classification model. The response by the organizations to the survey confirmed a substantial number of type-I errors. Furthermore, it revealed a positive association between the fitted probability of the text-based classification model and the organization’s response to the survey question on being an online platform organization. The survey results indicated that the text-based classification model can be used to obtain a subpopulation of potential platform organizations from the entire population of businesses with a website. This subpopulation may form a good starting point to study platform organizations in more detail.
我们开发了一个统计分类模型,用于根据在线平台组织网站上的文本对其进行识别。该模型随后被用于识别所有在荷兰商业登记中拥有网站的(潜在)平台组织。从单词和拟合概率的双峰分布来看,统计模型的经验结果是可信的,但结果表明高估了平台组织的数量。接下来,通过对统计分类模型确定为平台组织的组织进行调查,研究了结果的外部有效性。这些组织对调查的答复证实了大量的 I 类错误。此外,调查还显示,基于文本的分类模型的拟合概率与组织对 "是否为在线平台组织 "调查问题的答复之间存在正相关。调查结果表明,基于文本的分类模型可用于从所有拥有网站的企业中获取潜在平台组织的子群。这个子群可能是更详细研究平台组织的一个良好起点。
期刊介绍:
JOS is an international quarterly published by Statistics Sweden. We publish research articles in the area of survey and statistical methodology and policy matters facing national statistical offices and other producers of statistics. The intended readers are researchers or practicians at statistical agencies or in universities and private organizations dealing with problems which concern aspects of production of official statistics.