100k Rf Facebook.xlsx -

: Private Traits and Attributes are Predictable from Digital Records of Human Behavior (PNCAS). 2. Marketing & Reach Frequency (RF) Modeling

: Optimizing Facebook ad campaigns using Random Forest for ROI prediction. 100K RF FACEBOOK.xlsx

: Predicting personality or "Likes" using ensemble methods. : Private Traits and Attributes are Predictable from

: A "100K" dataset might contain performance metrics for 100,000 ad sets. The "RF" would refer to the Random Forest model used to determine which factors (bid price, creative, frequency) lead to the best conversion. 3. Fake News & Bot Detection : Predicting personality or "Likes" using ensemble methods

: Random Forest is preferred for 100K-row datasets because it handles high-dimensional data (many columns in an .xlsx) without the extensive preprocessing required by deep learning.

: Researchers frequently use Random Forest models to analyze large-scale CSV/XLSX exports of Facebook data to predict user attributes like age, gender, or political leaning.

Knowing the origin will help in finding the specific "deep paper" or documentation you need.