Accenture-Internship-Project

Project Information

Social Buzz, a rapidly growing social media and content creation platform is overcoming critical challenges. The company faces issues of managing immense data volumes, resource constraints despite its exponential growth, and the impending complexity of preparing for an Initial Public Offering (IPO). Founded in 2010 by former engineers from a prominent social media conglomerate, Social Buzz emphasizes content over individual user identity, garnering over 500 million active monthly users. With the majority of its workforce dedicated to technical operations, Social Buzz now seeks external expertise to navigate its scaling demands and ensure a successful transition to a publicly traded company.

Methodology

● Data sources: The primary data sources for the project are likely Social Buzz's internal databases or APIs, providing access to user engagement data and content categories.

● Data wrangling:

1. Data understanding

2. Data cleaning

3. Data manipulation

   ● Data analysis: 1. Finding the trends and patterns

   ● Data visualization

Data Analysis:

1. Identify Unique Posts and Categories: Count the number of unique posts and categories in the dataset.

2. Number of Reactions for Each Category: Calculate the total number of reactions for each category.

3. Analyze Sentiment for Each Category: Utilize sentiment analysis techniques to determine the sentiment associated with each category.

4. Month with Most Posts: Identify the month with the highest number of posts.

5. A number of Unique Reaction Types: Count the number of unique reaction types in the dataset.

6. Top Content-Type: Determine the most prevalent content type among the posts.

Concussion:

In summary, our analysis identified the top 5 content categories driving popularity on Social Buzz: Animals, Food, Healthy Eating, Science, and Technology. By understanding user sentiment and content preferences, Social Buzz can capitalize on these categories to enhance engagement and platform success. Implementing sentiment analysis tools and continuously monitoring content trends will be crucial for sustained growth and competitiveness in the social media landscape.