Data 4 Wildlife Hackathon 🛠️

Hackathon (29-30 Jan 2022) based on developing a digital solution to prevent illegal wildlife trade (IWT) on online social platforms.

• Team - Sean P. Rogers, Gabriela Youngken 👩‍🎓 👨‍🎓
• Mentor - Alastair Jamieson 👨‍🏫 (also API-keys holder 👛)

Challenge

• To build a benchmark dataset of possible instances of IWT & related information from online social platforms which could also be searched and analyzed 🔚
• According to challenge guidelines : Challenge1_Guidelines
  • A benchmark dataset is a public dataset which is designed and collected for studying real-world data science/research problems.
  • The benchmark dataset should be social media platform agnostic, as IWT happens across multiple platforms such as Instagram and YouTube.

Our Task

• Collect instagram posts with images related to Slow Loris hashtags (slowloris, slowlorisforsale) to build a benchmark dataset 🏛️

• Task Duration - 26 hours 🏃⏲️

Our Approach 🏗️

• Manually identify Slow Loris hashtags 🐵 for example data
• Call instagram api (RapidAPI, instagram85) for hashtag related feed
• Collect json (first page only), extract images & label images by user id
• Save images in folder labelled by language (see Future Prospects)
• Iterate api calls & collect images
• Import json to webpage, index.html, for human validation of images
• Manually validate images and export csv file with information from comments

Future Prospects 👀

• Call api recursively with 'next_page_id' to collect all pages
• Depending on image volume, project can evolve into Image Recognition for automation

Key Takeaways

• Focus on the bigger picture 🌄
• Build one-block-at-a-time 🧱
• Have consistent breaks 😌