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TIL: NNgroup UX Research, SponsorBlock, and Labella Python Library
NNgroup - UX Research Authority# · 2021-04-26 · via Stonecharioteer on Tech

NNgroup - YouTube

The Nielsen Norman Group’s YouTube channel - a goldmine of UX research and usability insights:

What They Offer:

  • Evidence-Based UX: Research-backed design principles
  • Usability Testing: Real user testing sessions and analysis
  • Design Patterns: Proven UI/UX patterns and best practices
  • Industry Insights: Current trends in user experience design
  • Expert Analysis: Jakob Nielsen and other UX authorities

Why It’s Valuable:

  • Founded by Jakob Nielsen (usability pioneer)
  • 40+ years of UX research
  • Scientific approach to design decisions
  • Practical, actionable insights for designers and developers

SponsorBlock - Skip over YouTube Sponsors

Brilliant crowdsourced solution for skipping sponsored content in YouTube videos:

How It Works:

  • Community Driven: Users mark sponsor segments in videos
  • Automatic Skipping: Browser extension automatically skips marked segments
  • Multiple Categories: Sponsors, intros, outros, self-promotion, etc.
  • Customizable: Choose which types of segments to skip
  • Privacy Focused: No tracking of viewing habits

Benefits:

  • Saves time on long-form content
  • Improves viewing experience
  • Community-maintained database
  • Works across devices with extensions

Labella - Label Positioning Library

labella · PyPI

Python library for solving the label overlap problem in data visualizations:

The Problem:

When creating charts with many data points, labels often overlap, making them unreadable.

Labella’s Solution:

  • Force Simulation: Uses physics-based algorithms to position labels
  • Overlap Avoidance: Ensures labels don’t overlap while staying near data points
  • Flexible Layout: Supports various chart types and orientations
  • Customizable: Adjust force parameters for different layouts

Use Cases:

  • Scatter plots with many points
  • Timeline visualizations
  • Network diagrams
  • Any chart where label positioning is challenging

Perfect for data scientists and visualization developers who need clean, readable charts.