Fixing Fieldnotes: Developing and Testing a Digital Tool for the Collection, Processing, and Analysis of Ethnographic Data

IF 3 2区 社会学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Social Science Computer Review Pub Date : 2023-12-18 DOI:10.1177/08944393231220488
Sofie L Astrupgaard, August Lohse, E. M. Gregersen, Jonathan H. Salka, Kristoffer Albris, Morten A. Pedersen
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Abstract

Ethnographic fieldnotes can contain richer and more thorough descriptions of social phenomena compared to other data sources. Their open-ended and flexible character makes them especially useful in explorative research. However, fieldnotes are typically highly unstructured and personalized by individual researchers, which make them harder to use as a method for data collection in collaborative and mixed methods research. More precisely, the unstructured nature of ethnographic fieldnotes presents three distinct challenges: 1) Organizability—it can be difficult to search and sort fieldnotes and thus to get an overview of them, 2) Integrability—it is difficult to meaningfully integrate fieldnotes with other more quantitative data types such as more such as surveys or geospatial data, and 3) Computational Processability—it is hard to process and analyze fieldnotes with computational methods such as topic models and network analysis. To solve these three challenges, we present a new digital tool, for the systematic collection, processing, and analysis of ethnographic fieldnotes. The tool is developed and tested as part of an interdisciplinary mixed methods pilot study on attention dynamics at a political festival in Denmark. Through case examples from this study, we show how adopting this new digital tool allowed our team to overcome the three aforementioned challenges of fieldnotes, while retaining the flexible and explorative character of ethnographic research, which is a key strength of ethnographic fieldwork.
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修复田野笔记:开发和测试用于收集、处理和分析人种学数据的数字工具
与其他数据来源相比,人种学田野笔记可以包含更丰富、更全面的社会现象描述。田野笔记的开放性和灵活性使其在探索性研究中尤为有用。然而,田野笔记通常高度非结构化,且由研究者个人定制,这使得它们更难用作合作研究和混合方法研究中的数据收集方法。更确切地说,人种学田野笔记的非结构化性质带来了三个不同的挑战:1)组织性--很难对田野调查笔记进行搜索和分类,因此也很难对其进行概述;2)整合性--很难将田野调查笔记与其他定量数据类型(如调查或地理空间数据)进行有意义的整合;3)计算处理性--很难使用计算方法(如主题模型和网络分析)对田野调查笔记进行处理和分析。为了解决这三个难题,我们提出了一种新的数字工具,用于系统地收集、处理和分析人种学田野笔记。该工具的开发和测试是一项跨学科混合方法试点研究的一部分,研究对象是丹麦政治节上的注意力动态。通过这项研究中的案例,我们展示了采用这一新的数字工具如何使我们的团队克服了上述三个田野笔记的挑战,同时保留了人种学研究的灵活性和探索性,而这正是人种学田野工作的一个关键优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Social Science Computer Review
Social Science Computer Review 社会科学-计算机:跨学科应用
CiteScore
9.00
自引率
4.90%
发文量
95
审稿时长
>12 weeks
期刊介绍: Unique Scope Social Science Computer Review is an interdisciplinary journal covering social science instructional and research applications of computing, as well as societal impacts of informational technology. Topics included: artificial intelligence, business, computational social science theory, computer-assisted survey research, computer-based qualitative analysis, computer simulation, economic modeling, electronic modeling, electronic publishing, geographic information systems, instrumentation and research tools, public administration, social impacts of computing and telecommunications, software evaluation, world-wide web resources for social scientists. Interdisciplinary Nature Because the Uses and impacts of computing are interdisciplinary, so is Social Science Computer Review. The journal is of direct relevance to scholars and scientists in a wide variety of disciplines. In its pages you''ll find work in the following areas: sociology, anthropology, political science, economics, psychology, computer literacy, computer applications, and methodology.
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