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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.23432 |
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| _version_ | 1866912161081589760 |
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| author | Brown, Megan A. Gruen, Andrew Maldoff, Gabe Messing, Solomon Sanderson, Zeve Zimmer, Michael |
| author_facet | Brown, Megan A. Gruen, Andrew Maldoff, Gabe Messing, Solomon Sanderson, Zeve Zimmer, Michael |
| contents | Scientists across disciplines often use data from the internet to conduct research, generating valuable insights about human behavior. However, as generative AI relying on massive text corpora becomes increasingly valuable, platforms have greatly restricted access to data through official channels. As a result, researchers will likely engage in more web scraping to collect data, introducing new challenges and concerns for researchers. This paper proposes a comprehensive framework for web scraping in social science research for U.S.-based researchers, examining the legal, ethical, institutional, and scientific factors that researchers should consider when scraping the web. We present an overview of the current regulatory environment impacting when and how researchers can access, collect, store, and share data via scraping. We then provide researchers with recommendations to conduct scraping in a scientifically legitimate and ethical manner. We aim to equip researchers with the relevant information to mitigate risks and maximize the impact of their research amidst this evolving data access landscape. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_23432 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Web Scraping for Research: Legal, Ethical, Institutional, and Scientific Considerations Brown, Megan A. Gruen, Andrew Maldoff, Gabe Messing, Solomon Sanderson, Zeve Zimmer, Michael Computers and Society Social and Information Networks Scientists across disciplines often use data from the internet to conduct research, generating valuable insights about human behavior. However, as generative AI relying on massive text corpora becomes increasingly valuable, platforms have greatly restricted access to data through official channels. As a result, researchers will likely engage in more web scraping to collect data, introducing new challenges and concerns for researchers. This paper proposes a comprehensive framework for web scraping in social science research for U.S.-based researchers, examining the legal, ethical, institutional, and scientific factors that researchers should consider when scraping the web. We present an overview of the current regulatory environment impacting when and how researchers can access, collect, store, and share data via scraping. We then provide researchers with recommendations to conduct scraping in a scientifically legitimate and ethical manner. We aim to equip researchers with the relevant information to mitigate risks and maximize the impact of their research amidst this evolving data access landscape. |
| title | Web Scraping for Research: Legal, Ethical, Institutional, and Scientific Considerations |
| topic | Computers and Society Social and Information Networks |
| url | https://arxiv.org/abs/2410.23432 |