# Third-Party Licenses and Attributions

This dataset, **PrivacySIM**, aggregates participant responses from five
previously published user studies into a single, unified schema. Each row's
`domain` column identifies the source study. The combined dataset is released
under [Creative Commons Attribution 4.0 International (CC BY 4.0)][cc-by-4.0];
per-row content remains under each source study's original license, summarized
below. **All five upstream licenses permit redistribution** as long as the
obligations in this file are met.

[cc-by-4.0]: https://creativecommons.org/licenses/by/4.0/legalcode

## Indication of changes

PrivacySIM modifies the upstream materials in the following ways. No underlying
participant responses are altered.

- Rows from the five source studies are concatenated and reshaped into a uniform
  schema: `user_id`, `domain`, `demographics`, `previous_experiences`,
  `privacy_attitudes`, `questionnaire`, `responses`, `preferences`.
- A deterministic `uuid5(NAMESPACE_URL, "<user_id>||<domain>")` identifier is
  added so downstream artifacts can join back to a participant.
- A 1,000-row sampled view (`dataset.csv`, 200 users per `domain` at
  `random_state=42`, with healthcare restricted to participants reporting on
  mental-health or medical information and informative previous-experience
  values) is published alongside the full 2,000-row aggregation
  (`full_dataset.csv`).
- Persona-conditioned prompt expansions (`dataset_with_prompts*.csv`) are
  generated by combining each user's persona facets with the original
  questionnaire text from the source study.

---

## 1. LLM Healthcare Consultation &nbsp;·&nbsp; `domain = LLM healthcare consultation`

**Source:** Liu, Z.; Hu, L.; Zhou, T.; Tang, Y.; Cai, Z.
*Prevalence Overshadows Concerns? Understanding Chinese Users' Privacy Awareness
and Expectations Towards LLM-Based Healthcare Consultation.*
**IEEE Symposium on Security and Privacy (S&P), 2025**, pp. 2716–2734.

**Repository:** <https://github.com/Cristliu/LLMHealthPrivacy_UserStudy>

**License:** **MIT License**

```
MIT License

Copyright (c) 2025 Cristliu

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
```

---

## 2. AI Agent Permissions &nbsp;·&nbsp; `domain = AI agent permissions`

**Source:** Wu, Y.; Yang, K.; Roesner, F.; Kohno, T.; Zhang, N.; Iqbal, U.
*Towards Automating Data Access Permissions in AI Agents.*
**arXiv:2511.17959**, 2025.

**Repository:** <https://github.com/llm-platform-security/ai-agent-permissions>

**License:** **Creative Commons Attribution 4.0 International (CC BY 4.0)**.
License text: <https://creativecommons.org/licenses/by/4.0/legalcode>

> Copyright (c) 2026 Yuhao Wu, Ke Yang, Franziska Roesner, Tadayoshi Kohno,
> Ning Zhang, Umar Iqbal. Licensed under [CC BY 4.0][cc-by-4.0].

**Modifications:** the original JSON-formatted user-study responses were parsed
into the unified PrivacySIM schema. No underlying participant responses were
altered.

---

## 3. LLM Chatbot &nbsp;·&nbsp; `domain = LLM chatbot`

**Source:** Tran, S.; Lu, H.; Slaughter, I.; Herman, B.; Dangol, A.; Fu, Y.;
Chen, L.; Gebreyohannes, B.; Howe, B.; Hiniker, A.; et al.
*Understanding Privacy Norms Around LLM-Based Chatbots: A Contextual Integrity
Perspective.*
**Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (AIES), 2025**,
vol. 8, no. 3, pp. 2522–2534.

**Replication data:** Tran, S.; Wolfe, R.; Weber, N. (2025). *Replication Data
for: Understanding Privacy Norms Around LLM-Based Chatbots: A Contextual
Integrity Perspective.* Harvard Dataverse, V1.
<https://doi.org/10.7910/DVN/M6ABJ3>

**License:** **Creative Commons Zero (CC0 1.0) public-domain dedication**.
Dedication text:
<https://creativecommons.org/publicdomain/zero/1.0/legalcode>

CC0 imposes no obligations on downstream users. We attribute the source as a
matter of academic practice.

**Modifications:** the cleaned factorial-vignette CSV was reshaped into the
unified PrivacySIM schema.

---

## 4. Chatbot Group Chat &nbsp;·&nbsp; `domain = Chatbot group chat`

**Source:** Chou, K.-H.; Wang, Y.-A.; Lau, C. K.; Sharif, M.; Hsiao, H.-C.
*Bot Among Us: Exploring User Awareness and Privacy Concerns About Chatbots in
Group Chats.*
**Proceedings on Privacy Enhancing Technologies (PoPETs), 2026**.

**Repository:** <https://github.com/csienslab/bot-among-us>

**License:** **MIT License**

```
MIT License

Copyright (c) 2025 Kai-Hsiang Chou, Yi-An Wang, Chong Kai Lau, Mahmood Sharif, Hsu-Chun Hsiao

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
```

---

## 5. LLM Conversational Agents &nbsp;·&nbsp; `domain = LLM conversational agents`

**Source:** Zufferey, N.; Abdelwahab Gaballah, S.; Marky, K.; Zimmermann, V.
*"AI is from the devil." Behaviors and Concerns Toward Personal Data Sharing
with LLM-based Conversational Agents.*
**Proceedings on Privacy Enhancing Technologies (PoPETs), 2025**,
vol. 2025, no. 3, pp. 5–28.

**Repository:** Open Science Framework, <https://osf.io/2vqws/>
(parent project: <https://osf.io/mqwjr/>).

**License:** **Creative Commons Attribution 4.0 International (CC BY 4.0)**.
License text: <https://creativecommons.org/licenses/by/4.0/legalcode>

> Copyright Noé Zufferey, Sarah Abdelwahab Gaballah, Karola Marky,
> Verena Zimmermann. Licensed under [CC BY 4.0][cc-by-4.0].

**Modifications:** the responses CSV was reshaped into the unified PrivacySIM
schema. Following the original authors' analysis we restrict to participants
who answered the chatbot-frequency questionnaire.

---

## License of the combined dataset

The combined dataset, PrivacySIM, is released under
**Creative Commons Attribution 4.0 International (CC BY 4.0)** —
<https://creativecommons.org/licenses/by/4.0/legalcode>.

CC BY 4.0 is compatible with all five upstream licenses: CC0 imposes no
constraints, the two CC BY 4.0 components are simply re-released under the
same license, and MIT permits redistribution provided that the original
copyright notices (above) are preserved.

Anyone redistributing or building on PrivacySIM must:

1. Provide attribution to PrivacySIM and to each upstream study they use.
2. Preserve this `THIRD_PARTY_LICENSES.md` file (or an equivalent that lists
   the same per-study attributions, license texts, and modification notices).
3. Indicate any further changes they make to the data.