# The Twitter Explorer: a Framework for Observing Twitter through Interactive Networks

arXiv: https://arxiv.org/abs/2003.03599 · HTML: https://mlsanity.com/paper/2003.03599/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Mar 2020.

## Built on by (most cited first, 2 of 2)

- [Defending Democracy: Using Deep Learning to Identify and Prevent Misinformation](https://mlsanity.com/paper/2106.02607/) (2021)
- [Extracting narrative signals from public discourse: a network-based approach](https://mlsanity.com/paper/2411.00702/) (2024)

## Abstract (arXiv)

We present an open-source interface for scientists to explore Twitter data through interactive network visualizations. Combining data collection, transformation and visualization in one easily accessible framework, the twitter explorer connects distant and close reading of Twitter data through the interactive exploration of interaction networks and semantic networks. By lowering the technological barriers of data-driven research, it aims to attract researchers from various disciplinary backgrounds and facilitates new perspectives in the thriving field of computational social science.