---
title: "towardsdatascience.com: AI citation standing"
description: "AI answer engines cited towardsdatascience.com in 34 of 29,566 measured answer runs (0.1%), on 5 of the 6 answer engines the Index measures, over 158 days of collection. That is #99 of 1095 classified editorial publications."
canonical: https://authoritytech.io/publications/towardsdatascience
---

# towardsdatascience.com: AI citation standing

AI answer engines cited towardsdatascience.com in 34 of 29,566 measured answer runs (0.1%), on 5 of the 6 answer engines the Index measures, over 158 days of collection. That is #99 of 1095 classified editorial publications.

Canonical URL: https://authoritytech.io/publications/towardsdatascience
Publication: towardsdatascience.com (towardsdatascience.com)
Source: Machine Relations Index, release 2026-10-21

## AI citation standing
- Citation rate: 0.1% of measured answer runs
- Answer runs citing it: 34 of 29,566 observed
- Answer engines citing it: 5 of 6 measured
- Collection dates: 158
- Rank: #99 of 1095 classified editorial publications
- All measured domains: #766 of 33,028
## Which AI engines cite towardsdatascience.com
Of the 6 answer engines the Machine Relations Index measures, Claude, Gemini, Google AI Mode, Google AI Overviews and Perplexity have cited towardsdatascience.com. ChatGPT has not cited it in a measured answer run yet. It was cited on 13 of the 158 days the Index collected answers in this window.
## Where towardsdatascience.com is cited most
| Category | Question shape | Citation rate | Cited / observed | Rank |
| --- | --- | --- | --- | --- |
| [AI Infrastructure](https://authoritytech.io/publications/ai-infrastructure-buyers.md) | problem-first questions | 5.3% | 12 / 225 | #10 of 422 |
| [AI Infrastructure](https://authoritytech.io/publications/ai-infrastructure-buyers.md) | head-to-head comparisons | 3.6% | 8 / 225 | #38 of 335 |
| [AI Security & Privacy](https://authoritytech.io/publications/ai-security-privacy-buyers.md) | head-to-head comparisons | 2.6% | 6 / 232 | #52 of 367 |
| [AI Infrastructure](https://authoritytech.io/publications/ai-infrastructure-buyers.md) | how-to-choose questions | 1.3% | 3 / 226 | #115 of 387 |
| [AI Infrastructure](https://authoritytech.io/publications/ai-infrastructure-buyers.md) | is-it-worth-it questions | 0.9% | 2 / 225 | #164 of 378 |
| Legacy News Topics | news and topic questions | 0.1% | 1 / 2,066 | #3,680 of 4,017 |
| [AI Infrastructure](https://authoritytech.io/publications/ai-infrastructure-buyers.md) | best-in-category questions | 0.5% | 1 / 197 | #318 of 331 |
| [AI Infrastructure](https://authoritytech.io/publications/ai-infrastructure-buyers.md) | top-list questions | 0.4% | 1 / 228 | #388 of 403 |
## Is a placement here worth pursuing?
Getting into towardsdatascience.com and becoming known for the right thing are different results. Coverage helps your position in AI answers when the article ties your company to a specific claim your buyers ask about, in a publication engines already cite on that question. The Index sees towardsdatascience.com cited most on problem-first questions in AI Infrastructure (#10 of 422 sources cited on those answers), so that is where its standing is relevant.

You can pursue it yourself: find the editor or writer who covers your topic in towardsdatascience.com's recent bylines and pitch one specific, sourced angle. Either way, settle first what you want to be known for, and make the piece say it in terms specific enough for an engine to attach to your company; a general category explainer rarely does that.

An agency is worth it when you want several pieces to build one position rather than land a single article, or when you lack the time, the editor contacts or the writing to make each piece say the right thing. AuthorityTech, which publishes this page, is that kind of agency: it works out the narrative with you, picks the angle and the outlets already cited on your buyers' questions, writes the content, pitches and places it, and measures what AI engines cite afterwards, the practice it calls Machine Relations. No one can promise what an AI engine will cite, and nothing here implies towardsdatascience.com endorses AuthorityTech.
## How this is measured
Every citation figure is the Machine Relations Index's, carried with its own denominator. AuthorityTech does not compute them. The Index runs buyer questions against 6 answer engines. Release 2026-10-21, methodology mri_score_v2.1. The Index's own profile of towardsdatascience.com: [towardsdatascience.com in the Machine Relations Index](https://machinerelations.ai/index/domains/towardsdatascience.com).
Window: 2026-05-10 to 2026-10-21, 158 days of collection.
Evidence floor for a published rank: 10 observations across 7 collection dates.

## Links

- [All ranked publications](https://authoritytech.io/publications.md)
- [Machine Relations Index](https://machinerelations.ai/machine-relations-index)
- [towardsdatascience.com in the Machine Relations Index](https://machinerelations.ai/index/domains/towardsdatascience.com)
- [How to compare AI PR agencies](https://authoritytech.io/blog/best-ai-pr-agencies-2026.md)
- [What is Machine Relations](https://machinerelations.ai/glossary/machine-relations)