Objective: To analyze the timing of Facebook posts from the ISAP – Computer Engineering Department and investigate how posting time affects user engagement.
Background: The timing of social media posts can have a significant impact on engagement. Understanding the optimal times for posting can lead to more effective communication and outreach. This activity focuses on analyzing when posts are made and how the timing correlates with engagement metrics.
- Provided dataset containing Facebook post details, including “Publish time” and engagement metrics.
- Access to data analysis software (e.g., Excel).
1. Time Slot Categorization:
a. Convert the “Publish time” to local time.
b. Categorize posts into different time slots (e.g., Morning, Noon, Afternoon, Evening, Night).
c. Count the number of posts in each time slot.
Morning: 06:00AM to 11:00AM
Noon: 11:01AM to 02:00PM
Afternoon: 02:00PM to 06:00PM
Evening: 06:01PM to 07:00PM
Night: 07:01PM to 05:59AM
2. Engagement Analysis by Time Slot:
a. Calculate the average “People Reached” for each time slot.
b. Identify the time slot with the highest and lowest average engagement.
3. Day of the Week Analysis:
a. Categorize posts by the day of the week.
b. Calculate the average “People Reached” for each day.
c. Identify the day with the highest engagement.
a. Create a bar chart comparing the average “People Reached” across different time slots.
b. Plot a line chart showing engagement trends throughout the week.
5. Interpretation and Recommendations:
a. Interpret the findings and identify patterns in posting times and engagement.
b. Provide recommendations for optimal posting times to maximize engagement.
c. Discuss any limitations of the analysis and propose further areas of investigation.
- A written report summarizing the analysis, findings, visualizations, and recommendations.
- A brief presentation to share insights with peers or stakeholders.
- Accuracy and thoroughness of the analysis.
- Clarity and relevance of the visualizations.
- Practicality and insightfulness of the recommendations.
- Quality of the written report and presentation.
- Estimated time for completion: 3-4 hours.
- Data Analysis: Excel, Python (using Pandas and Matplotlib or Seaborn libraries).
- Report Writing: Microsoft Word, Google Docs.
- Presentation: PowerPoint, Google Slides, Canva.