An Empirical Study on Compliance with Ranking Transparency in the Software Documentation of EU Online Platforms
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2023
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| Subjects: | |
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| _version_ | 1866910305737506816 |
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| author | Sovrano, Francesco Lognoul, Michaël Bacchelli, Alberto |
| author_facet | Sovrano, Francesco Lognoul, Michaël Bacchelli, Alberto |
| contents | Compliance with the European Union's Platform-to-Business (P2B) Regulation is challenging for online platforms, and assessing their compliance can be difficult for public authorities. This is partly due to the lack of automated tools for assessing the information (e.g., software documentation) platforms provide concerning ranking transparency. Our study tackles this issue in two ways. First, we empirically evaluate the compliance of six major platforms (Amazon, Bing, Booking, Google, Tripadvisor, and Yahoo), revealing substantial differences in their documentation. Second, we introduce and test automated compliance assessment tools based on ChatGPT and information retrieval technology. These tools are evaluated against human judgments, showing promising results as reliable proxies for compliance assessments. Our findings could help enhance regulatory compliance and align with the United Nations Sustainable Development Goal 10.3, which seeks to reduce inequality, including business disparities, on these platforms. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2312_14794 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | An Empirical Study on Compliance with Ranking Transparency in the Software Documentation of EU Online Platforms Sovrano, Francesco Lognoul, Michaël Bacchelli, Alberto Software Engineering Artificial Intelligence Compliance with the European Union's Platform-to-Business (P2B) Regulation is challenging for online platforms, and assessing their compliance can be difficult for public authorities. This is partly due to the lack of automated tools for assessing the information (e.g., software documentation) platforms provide concerning ranking transparency. Our study tackles this issue in two ways. First, we empirically evaluate the compliance of six major platforms (Amazon, Bing, Booking, Google, Tripadvisor, and Yahoo), revealing substantial differences in their documentation. Second, we introduce and test automated compliance assessment tools based on ChatGPT and information retrieval technology. These tools are evaluated against human judgments, showing promising results as reliable proxies for compliance assessments. Our findings could help enhance regulatory compliance and align with the United Nations Sustainable Development Goal 10.3, which seeks to reduce inequality, including business disparities, on these platforms. |
| title | An Empirical Study on Compliance with Ranking Transparency in the Software Documentation of EU Online Platforms |
| topic | Software Engineering Artificial Intelligence |
| url | https://arxiv.org/abs/2312.14794 |