CIB Mango Tree
A Civic Tech DC Project
Time-Frequency Analysis
This test will show when new posts (aka data entries) in your dataset were made. You can view the frequency of posts over a 24-hour period using either the output file or bar graph, making it easy to spot any unusual patterns.
Test Process:
Set Time Window Length: Start by specifying the desired length of time windows for the 24-hour period (recommended: 30 minutes).
Tally Posts: The test will count the posts made in each time window across your dataset. For example, with a 30-minute window, it will count posts from 12:00 AM to 12:30 AM, 12:30 AM to 1:00 AM, and so on.
Graph Results: Finally, the test will display these frequencies in a CSV file and bar chart, with each bar representing a specific time window across the 24-hour period.
Tally Posts: The test will count the posts made in each time window across your dataset. For example, with a 30-minute window, it will count posts from 12:00 AM to 12:30 AM, 12:30 AM to 1:00 AM, and so on.
Graph Results: Finally, the test will display these frequencies in a CSV file and bar chart, with each bar representing a specific time window across the 24-hour period.
Option 1: CSV Output Format
The test will produce a .csv file that provides the numerical tallies of posts for each given time window in the 24-hour period.
Option 2: Bar Chart
The test will also produce a link to a dashboard that can be run locally in your browser (this dashboard does not involve a connection to the internet).
The dashboard will render the 24-hour graph of post frequency.
References
- Github Code:
- Inspiration: Influencing Overseas Chinese by Tweets: Text-Images as the Key Tactic of Chinese Propaganda