Social Connections on User Retention

Requirements Clarification & Assessment

1. Define "Active User":

   • Clarify what criteria define an "active user." Is it based on login frequency, content interaction, or time spent on the platform?

2. Data Availability:

   • Identify what data is available and accessible for analysis. Key data points include:
     • Number of friends at the start and end of the period.
     • User activity metrics (logins, posts, comments).
     • Demographic information (location, age, etc.).
     • Account age and historical activity data.

3. Scope of Analysis:

   • Determine the time frame for the analysis (e.g., six months) and any specific cohorts (e.g., users who joined before a certain date).

4. Potential Confounding Variables:

   • Assess other factors that might influence user retention, such as account age, initial engagement level, or demographic factors.

5. Hypothesis Formulation:

   • Null Hypothesis (H0): There is no significant relationship between the number of friends and user retention.
   • Alternative Hypothesis (H1): A larger number of friends increases the likelihood of user retention.

6. Data Cleaning and Preparation:

   • Ensure data quality by addressing missing values, outliers, and inconsistencies.

7. Statistical and Machine Learning Methods:

   • Decide on the appropriate statistical tests or machine learning models to use, such as logistic regression or decision trees.

8. Ethical Considerations:

   • Ensure compliance with privacy regulations and ethical standards in data handling.