# A Web Scraping Methodology for Bypassing Twitter API Restrictions

arXiv: https://arxiv.org/abs/1803.09875 · HTML: https://mlsanity.com/paper/1803.09875/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Mar 2018.

## Built on by (most cited first, 3 of 3)

- [Machine learning and emoji prediction: How much accuracy can MARBERT achieve?](https://mlsanity.com/paper/2604.21108/) (2026)
- [Transfer Learning Approach for Detecting Psychological Distress in Brexit Tweets](https://mlsanity.com/paper/2102.00912/) (2021)
- [Russo-Ukrainian War: Prediction and explanation of Twitter suspension](https://mlsanity.com/paper/2306.03502/) (2023)

## Abstract (arXiv)

Retrieving information from social networks is the first and primordial step many data analysis fields such as Natural Language Processing, Sentiment Analysis and Machine Learning. Important data science tasks relay on historical data gathering for further predictive results. Most of the recent works use Twitter API, a public platform for collecting public streams of information, which allows querying chronological tweets for no more than three weeks old. In this paper, we present a new methodology for collecting historical tweets within any date range using web scraping techniques bypassing for Twitter API restrictions.