{"title":"超越厚重数据的人种学","authors":"Ajda Pretnar Žagar, Dan Podjed","doi":"10.1111/napa.12226","DOIUrl":null,"url":null,"abstract":"This article presents opportunities for enriching anthropological knowledge and methods with machine learning and data analysis. Different examples show how quantitative methods empower anthropologists and how computational methods supplement ethnography, from sensor data and interview transcripts to designing technology solutions and automatically labeling cultural heritage. Conversely, the authors discuss the benefits of qualitative approaches in contemporary anthropological research and show how to transition from data analysis to ethnography and <jats:italic>vice versa</jats:italic>. Finally, the article pinpoints aspects in which each method can fail individually. It discusses why a combination of the two approaches, called circular mixed methods, minimizes the chance of failure and maximizes insights from the data.","PeriodicalId":45176,"journal":{"name":"Annals of Anthropological Practice","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Ethnography beyond thick data\",\"authors\":\"Ajda Pretnar Žagar, Dan Podjed\",\"doi\":\"10.1111/napa.12226\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents opportunities for enriching anthropological knowledge and methods with machine learning and data analysis. Different examples show how quantitative methods empower anthropologists and how computational methods supplement ethnography, from sensor data and interview transcripts to designing technology solutions and automatically labeling cultural heritage. Conversely, the authors discuss the benefits of qualitative approaches in contemporary anthropological research and show how to transition from data analysis to ethnography and <jats:italic>vice versa</jats:italic>. Finally, the article pinpoints aspects in which each method can fail individually. It discusses why a combination of the two approaches, called circular mixed methods, minimizes the chance of failure and maximizes insights from the data.\",\"PeriodicalId\":45176,\"journal\":{\"name\":\"Annals of Anthropological Practice\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2024-09-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annals of Anthropological Practice\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1111/napa.12226\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ANTHROPOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Anthropological Practice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1111/napa.12226","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ANTHROPOLOGY","Score":null,"Total":0}
This article presents opportunities for enriching anthropological knowledge and methods with machine learning and data analysis. Different examples show how quantitative methods empower anthropologists and how computational methods supplement ethnography, from sensor data and interview transcripts to designing technology solutions and automatically labeling cultural heritage. Conversely, the authors discuss the benefits of qualitative approaches in contemporary anthropological research and show how to transition from data analysis to ethnography and vice versa. Finally, the article pinpoints aspects in which each method can fail individually. It discusses why a combination of the two approaches, called circular mixed methods, minimizes the chance of failure and maximizes insights from the data.