SMDT — Social Media Data Toolkit

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SMDT: Social Media Data Toolkit|

API Reference
Recipes
Paper
arXiv

Data Standardization

Unified schemas for Twitter, Reddit, Bluesky, Telegram, and more.

Content Enrichment

Powerful pipelines for NLP, toxicity detection, and entity extraction.

Network Analysis

Built-in tools for constructing and analyzing social graphs.

What is SMDT? ​

SMDT (Social Media Data Toolkit) is a comprehensive Python library designed to streamline the ingestion, standardization, and analysis of social media data. It provides a unified interface for handling data from diverse platforms, enabling researchers to focus on analysis rather than data wrangling.

Why use SMDT? ​

  • Unified Schema: Convert messy JSON dumps from various platforms into a consistent, queryable format.
  • Modular Design: Easily plug in new data readers, enrichers, or analysis modules.
  • Research Ready: Built specifically for computational social science workflows, supporting reproducibility and scalability.

Citation ​

If you use SMDT in your research, please cite the following paper:

bibtex
@article{NAJAFI2026100356,
    title = {Social Media Data Toolkit: Standardization and pseudonymization of social network datasets},
    journal = {Online Social Networks and Media},
    volume = {55},
    pages = {100356},
    year = {2026},
    issn = {2468-6964},
    doi = {https://doi.org/10.1016/j.osnem.2026.100356},
    url = {https://www.sciencedirect.com/science/article/pii/S2468696426000121},
    author = {Ali Najafi and Letizia Iannucci and Mikko Kivelä and Onur Varol},
    keywords = {Computational social science, Cross-platform analysis, Data standardization, Data pseudonymization, Social media analytics, Network analysis, Natural Language Processing}
}