Wikipedia Web Traffic Prediction
Comparative time-series forecasting study on 145,000 Wikipedia articles — co-authored research paper under revision
| Research Paper (Under Revision) | Co-authored with Prof. Sandhya Avasthi, ABES Engineering College, India | 2025 |
Overview
Conducted a comparative study of 7 time-series forecasting models on a 145,000-article Wikipedia Kaggle dataset, evaluated using RMSE as the primary performance metric.
Models Compared
- Moving Average
- Exponential Smoothing
- ARMA
- ARIMA
- Auto-ARIMA
- Prophet
- LSTM
Key Finding
Identified Moving Average as the best-performing model — demonstrating that simpler statistical models outperformed deep learning (LSTM) on this task, providing practical model selection insights for large-scale web traffic forecasting.
Collaboration
Co-authored with international academic collaborator across two institutions (BatStateU, Philippines & ABES Engineering College, India). Submitted to journal, currently under revision.
Tech Stack: R · Time-Series Analysis · ARIMA · Prophet · LSTM · Kaggle