### Explanation Social media platforms record and expose various types of user activity, from obvious actions like posts and comments to subtle interactions like reactions or viewing stories. The frequency, timing, and patterns of this activity can reveal information about a user's behavior, relationships, and even authenticity. Statistical analysis of activity patterns can help identify automated accounts (bots), determine a user's active hours and timezone, or map their social connections through interaction patterns. ### Examples - [Learning to Track Disinformation and Bot Activity in Twitter](https://www.raebaker.net/blog/2020/05/27/learning-to-track-disinformation-and-bot-activity-in-twitter) ### Types - behavioural - technical ### See also - [[SOWEL-2. Producing Social Graph]] - [[SOWEL-3. Creating Content]] ### Typical techniques - [[SOTL-5.1. Check Initial Activity]] - [[SOTL-5.2. Analyse Sentiments]] - [[SOTL-5.3. Detect Close Relations By Interactions]] - [[SOTL-5.4. Study Time Of Posts And Actions]] - [[SOTL-5.5. Study Activity At The Same Time]] - [[SOTL-5.6. Analyze Content With Word Clouds]] - [[SOTL-5.7. Display Activity On A Timeline]] - [[SOTL-5.8. Check Minor Functionality]]