从理论到实践:为社会科学研究收集社交媒体数据的见解和障碍。

IF 2.4 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Frontiers in Big Data Pub Date : 2024-05-30 eCollection Date: 2024-01-01 DOI:10.3389/fdata.2024.1379921
Yan Chen, Kate Sherren, Kyung Young Lee, Lori McCay-Peet, Shan Xue, Michael Smit
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引用次数: 0

摘要

社交媒体深刻地改变了我们的自我表达、交流和参与公共讨论的模式,产生了大量的对话和内容,涵盖了我们社会生活的方方面面。因此,社交媒体平台作为识别社会趋势和现象的数据来源变得越来越重要。近年来,随着技术公司对应用程序编程接口(API)设置更多限制或完全关闭公共 API,学术界在获取社交媒体数据方面逐渐失去了优势。在这种情况下,许多利用此类数据研究公益问题的社会科学家的工作被迫中断。我们考虑了八种基于图像的社交媒体数据收集方法的可行性:数据慈善组织、数据存储库、数据捐赠、第三方数据公司、自制工具以及各种网络刮擦工具和脚本。本文从文献和作者的经验出发,讨论了这些方法的优势和挑战。最后,我们讨论了改进社交媒体数据收集的机制,这些机制将使这一社会科学研究的未来前沿得以实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
From theory to practice: insights and hurdles in collecting social media data for social science research.

Social media has profoundly changed our modes of self-expression, communication, and participation in public discourse, generating volumes of conversations and content that cover every aspect of our social lives. Social media platforms have thus become increasingly important as data sources to identify social trends and phenomena. In recent years, academics have steadily lost ground on access to social media data as technology companies have set more restrictions on Application Programming Interfaces (APIs) or entirely closed public APIs. This circumstance halts the work of many social scientists who have used such data to study issues of public good. We considered the viability of eight approaches for image-based social media data collection: data philanthropy organizations, data repositories, data donation, third-party data companies, homegrown tools, and various web scraping tools and scripts. This paper discusses the advantages and challenges of these approaches from literature and from the authors' experience. We conclude the paper by discussing mechanisms for improving social media data collection that will enable this future frontier of social science research.

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来源期刊
CiteScore
5.20
自引率
3.20%
发文量
122
审稿时长
13 weeks
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