---
# System prepended metadata

title: P6

---

# P6

:::warning
This is a template to be individually filled by each FAIR4RS participant. Coloured boxes provide guidelines and can be removed when no longer needed. 

You can have a look at [this example](https://hackmd.io/@fair4rs/SybbutV26/%2FvjcLJbnxTei8cDhawj02QA) from a previous edition of the program.
:::

# FAIR4RS Project: 

**Name: Shuyu Zhang

**Project Name: Retrieving social media data from TikTok research API

**Code Repository: [TIKTOK-API on GitHub]()**
[https://github.com/hadyyu/tiktok-api]

**Scientific and Software Background**: 
l am a 2nd year PhD at Urbanism department, ABE, working with social media and platform placemaking. l have some experience in data analysis with R and Python, and recently started using Json and shell to retrieve data from TikTok research API. I am a beginner on github and be glad to create my first github repository.

**Project Description:** 
The aim of this project is to build the framework and clear structure to retrieve video descriptions, comments and users information data from TikTok research API, as well as to store, query and analyse the data in the later stage.


**Project goals**
Guides for retrieving data from TikTok research API.
Try to identity pieces of code that could have functional blocks and easily tested.
Work with environment variables and use an env file.
Use sqlite or other methods to easily and structurely to store and query data.
Have R scripts for extracting data and later analysis.
Use the readme to describe how to work with the database and to describe the workflow.

## Progress Update
:::info
Throughout the FAIR4RS program, we'll work on a git repository. Improvements can be noticed comparing the [original version](https://github.com/hadyyu/tiktok-api/tree/f51b0f1c45197d7d6bae3bceb53e004446f3d403) with the [updated version](https://github.com/hadyyu/tiktok-api). 

**Repository Project Management**
- [Project board](https://github.com/hadyyu/tiktok-api)

**Code Structure**
- Created [fuction](https://github.com/hadyyu/tiktok-api/blob/main/retrieve_comments.sh) in the codes to make code structure more clear

**Documentation**

- Created a [readme file](https://github.com/hadyyu/tiktok-api/blob/main/README.md).

 
**Testing**
- Added [test](https://github.com/hadyyu/tiktok-api/blob/main/test.json)cases.


**License & Citations**
- Added a [CITATION file]()
- Included a [LICENSE file](https://github.com/hadyyu/tiktok-api/tree/main?tab=MIT-1-ov-file)


## Future Plans
:::info
The future aim of the project is to store those retrieved data structurely and analyse them within the different research questions.
:::

- [ ] Try to use sqlite or other tools to help storing and querying those data, especially for videos and images
- [ ] Transform the data format, such as videos to images, videos to audios to texts
- [ ] Analyse the multimodal data

By following this plan, I aim to search for tools and API applications to analyses and make new repositories.


---
## Feedback for the FAIR4RS program
:::    success
This program is still a pilot, the questions below are meant to give an idea about the relevance and effectiveness of this program. We will later send a survey with more specific questions.
:::

**Top**
- The course are well-structured with online tutorials of basic knowledge and offline personal meeting with practicing of own research project.

**Tip**
- Structure is the most important thing when facing big data and complex code.
 
**General impression:** Super useful for the beginners to build up first repostitory and get a comprehensive understanding of FAIR4RS.

**Expectations met:** Github tutorial and face to face meeting which solving lots of questions.

**Useful content:** Code Refinery workshop, practical examples, and DCC meeting.

**Content improvement:** Provide more good examples and cases to increase understanding.

**Effective activities:** Hands-on project work, guidance from mentors, and tutorials and practices on github.

**Improvement in activities and scheduling:** The online courses have intensive schedule which may not accommodate participants' availability.