Executive Summary :
The analysis of social Buzz data provides valuable insights into popular categories and posting trends. The top 5 categories, including Animals, Science, Healthy Eating, Food, and Technology, collectively represent 36% of total posts. Moreover, may exhibits the highest posting activity, with a noticeable decline from January to February. Understanding these trends is essential for strategic decision-making and content planning, allowing for tailored content strategies and resource allocation to maximize impact across different categories to increase traffic.
Problem statement :
The objective is to utilize regular expressions to identify and analyze the most popular content categories. This analysis aims to support content planning strategies geared towards increasing viewership.
Tasks performed :
Data Wrangling : Cleaning the data by removing rows that have values which are missing, changing the data type of some values within a column, and removing columns which are not relevant to this task, ended with three cleaned data sets and merged into one dataset. Removes punctuation and special characters where needed using regex.
Exploratory Data Analysis (EDA) :
- Created visualizations: charts, graphs, heat maps, and plots to uncover patterns, trends, and anomalies.
Data Analysis and Interpretation
- Applied analytical techniques, performed category count, postings count, sort data in descending order to analyze and highlight key trends.
Results
Key Insights:
Top 5 Popular Categories: The analysis highlights the top 5 most popular categories, namely Animals, Science, Healthy Eating, Food, and Technology, collectively representing 36% of the total posts.
Seasonal Posting Trends: Month May demonstrates the highest posting activity, while a noticeable decline occurs from January to February. Understanding the factors driving these fluctuations in high and low activity months, such as May and February, is essential for informed content planning and strategic decision-making.
Recommendations :
Leveraging these insights can significantly impact strategic decision-making and content planning. Delving into the reasons behind posting fluctuations in specific months can optimize content strategies, enhance engagement efforts, and allocate resources effectively across various categories and time frames.