Exploring Viral Patterns & Social Media Trends (2020-2025)
A comprehensive exploratory data analysis of trending hashtags on Twitter/X from 2020 to 2025. This project analyzes over 12,000 trending entries to uncover patterns in viral content, major world events, and social media engagement metrics.
Using Python, Pandas, and data visualization libraries, I examined temporal patterns, identified peak trending periods, and analyzed how major global events influenced social media conversations.
Analysis of trending activity across six years (2020-2025). Shows consistent high engagement from 2020-2023, with a notable decline in 2024-2025 as the dataset approaches present day.
The most viral hashtags over the entire period. Dominated by major cultural figures (Kanye, Trump), holidays (New Year, Thanksgiving), and global events (Ukraine, Israel/Gaza, Iran).
Temporal patterns revealing seasonal variations in trending activity. March and July show consistently high engagement across multiple years, while late 2024 shows decreased activity.
Aggregate monthly analysis shows March, January, and May as peak months for viral content, likely driven by seasonal events and new year momentum.
Trending activity shows relatively consistent patterns throughout the week, with slight increases mid-week (Tuesday-Thursday) as major news cycles peak.
Distribution analysis reveals a heavily right-skewed pattern, with most trending topics garnering moderate engagement while a small number achieve massive viral reach (10M+ tweets).
Year-by-year breakdown of the top 10 trending hashtags, showing the evolution of viral content from COVID-dominated 2020-2021 to more diverse topics in recent years.