Skip to content

Repository files navigation

Facebook Metrics - Statistical Data Analysis

Analysis of UCI Facebook Metrics Dataset using statistical methods.

Dataset

The UCI Facebook Metrics is an open-source dataset containing data about all the posts from a particular Facebook page over a period of time. It contains 500 observations and 19 features, with 7 features being information that are available at the time of posting, and the rest, based on a post's performance.

Project:

  1. Exploratory Data Analysis (EDA)
  2. Principal Component Analysis (PCA)
  3. Regression Modelling
  4. Observation

Source:

https://archive.ics.uci.edu/ml/datasets/Facebook+metrics

(Moro et al., 2016) Moro, S., Rita, P., & Vala, B. (2016). Predicting social media performance metrics and evaluation of the impact on brand building: A data mining approach. Journal of Business Research, 69(9), 3341-3351.

About

Statistical Data Analysis on Facebook Metrics UCI dataset. EDA, PCA, and Regression Models for prediction.

Topics

Resources

Stars

0 stars

Watchers

1 watching

Forks

Contributors

Languages