---
title: "Slashdot: AI citation standing"
description: "AI answer engines cited Slashdot in 33 of 28,201 measured answer runs (0.1%), on 6 of the 6 answer engines the Index measures, over 157 days of collection. That is #96 of 1039 classified editorial publications."
canonical: https://authoritytech.io/publications/slashdot
---

# Slashdot: AI citation standing

AI answer engines cited Slashdot in 33 of 28,201 measured answer runs (0.1%), on 6 of the 6 answer engines the Index measures, over 157 days of collection. That is #96 of 1039 classified editorial publications.

Canonical URL: https://authoritytech.io/publications/slashdot
Publication: Slashdot (slashdot.org)
Source: Machine Relations Index, release 2026-10-20

## AI citation standing
- Citation rate: 0.1% of measured answer runs
- Answer runs citing it: 33 of 28,201 observed
- Answer engines citing it: 6 of 6 measured
- Collection dates: 157
- Rank: #96 of 1039 classified editorial publications
- All measured domains: #770 of 32,242
## Which AI engines cite Slashdot
All 6 answer engines the Machine Relations Index measures have cited Slashdot: ChatGPT, Claude, Gemini, Google AI Mode, Google AI Overviews and Perplexity. It was cited on 25 of the 157 days the Index collected answers in this window.
## Where Slashdot is cited most
| Category | Question shape | Citation rate | Cited / observed | Rank |
| --- | --- | --- | --- | --- |
| Legacy News Topics | news and topic questions | 0.6% | 12 / 2,066 | #293 of 4,017 |
| [Fintech](https://authoritytech.io/publications/fintech-buyers.md) | news and topic questions | 0.7% | 4 / 593 | #308 of 1,528 |
| [Martech & Advertising](https://authoritytech.io/publications/martech-advertising-buyers.md) | news and topic questions | 0.7% | 4 / 578 | #266 of 1,243 |
| [Logistics & Freight](https://authoritytech.io/publications/logistics-freight-buyers.md) | best-in-category questions | 3.7% | 4 / 107 | #52 of 213 |
| [Cybersecurity](https://authoritytech.io/publications/cybersecurity-buyers.md) | news and topic questions | 0.5% | 3 / 599 | #394 of 1,338 |
| [Fintech](https://authoritytech.io/publications/fintech-buyers.md) | top-list questions | 1.1% | 2 / 183 | #153 of 268 |
| [Cybersecurity](https://authoritytech.io/publications/cybersecurity-buyers.md) | best-in-category questions | 0.5% | 1 / 194 | #260 of 292 |
| [Enterprise Software](https://authoritytech.io/publications/enterprise-software-buyers.md) | top-list questions | 0.6% | 1 / 177 | #324 of 364 |
## Is a placement here worth pursuing?
Getting into Slashdot 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 Slashdot cited most on news and topic questions in Fintech (#308 of 1,528 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 Slashdot'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 Slashdot 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 2026-10-20, methodology mri_score_v2.1. The Index's own profile of slashdot.org: [Slashdot in the Machine Relations Index](https://machinerelations.ai/index/domains/slashdot.org).
Window: 2026-05-10 to 2026-10-20, 157 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)
- [Slashdot in the Machine Relations Index](https://machinerelations.ai/index/domains/slashdot.org)
- [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)