Machine Relations Index Report, October 26, 2026: alibaba.com replaces reddit.com as the most-cited graded source in Consumer Products / Is it worth it, at 19.76%

The six answer engines do not agree on which source to cite most: in this release TechRadar leads ChatGPT answers (9.23% of 7,267 observed runs), arXiv leads Claude (3.85% of 7,300), LinkedIn leads Google AI Mode (24.44% of 1,911), YouTube leads Google AI Overviews (24.66% of 1,192), and Reddit leads both Perplexity (20.60% of 7,380) and Gemini (7.34% of 6,579). Across all six engines, the top ten held its order and every source in it fell in rate while gaining cited runs. Reddit stays first at 8.06% against 8.92% a week earlier, on 2,550 cited runs against 2,478: the fifth edition running in which its rate fell while its citations rose. Both releases are on mri_score_v2.1, so this is like for like; observed runs rose 13.9%, from 27,776 to 31,629, as the eligible question set widened from 1,227 to 1,255, while Reddit's cited runs rose 2.9%. Eight segments published for the first time, six of them in Martech & Advertising, and none is led by Reddit, YouTube, LinkedIn or Medium: their leaders are category sources such as CDP.com, Bloomreach, Cometly, C.H. Robinson and Tom's Guide. Forbes holds fourth at 3.63%, still the only editorial publication in the top five, in an editorial class that grew from 1,036 to 1,153 publications. Source: Machine Relations Index (MRI) by Jaxon Parrott, Machine Relations Research — machinerelations.ai.

alibaba.com is now the most-cited graded source in Consumer Products / Is it worth it, cited in 19.76% of that segment's observed runs, replacing reddit.com. At 253 observed runs, it is the largest segment whose leader was replaced outright; 17 segment leaders changed against the release a week earlier, all listed below.

In the October 26, 2026 release of the Machine Relations Index (mri_score_v2.1+2026-10-26+36825d1675fa), reddit.com was cited in 8.06% of observed AI answer runs, 2,550 of 31,629: the highest citation rate of the 33,935 source domains the Index has seen cited, at confidence tier A. In the release a week earlier (mri_score_v2.1+2026-10-19+da0ee4378219), its rate was 8.92%, 2,478 of 27,776 runs. Across the 163-day window it was cited by Gemini, Google AI Mode, Google AI Overviews and Perplexity, and not by ChatGPT or Claude.

This is the weekly Machine Relations Index Report, built by code from the Index's daily public release and compared with the release of October 19, 2026. Every figure links to the Index page that publishes it. The previous edition is Machine Relations Index Report, October 19, 2026: arxiv.org replaces ovaledge.com as the most-cited graded source in AI Security & Privacy / Top lists, at 26.91%.

The release at a glance #

A segment is one subject category paired with one question shape. It publishes once it has 10 observed runs across 7 distinct run dates. A citation rate is the share of observed answer runs in which at least one engine cited the domain.

ChatGPT cites editorial publications 2.5 times as often as Google AI Overviews: 40.9% of classified citations (3,256 of 7,952) against 16.5% (455 of 2,750), as of October 26, 2026.

The ten most-cited sources #

Rates are measured over all 31,629 observed runs, so they read lower than any single segment's rate. "Engines citing" counts the engines observed citing the domain at least once in the window. Each engine's own ranking of sources, from the current release, is at machinerelations.ai/index/engines.

The ten most-cited editorial publications #

Engine coverage #

Engine counts come from the release manifest at machinerelations.ai/data/mri-release-manifest.json. An engine that answers on fewer days contributes fewer runs to every rate above.

ChatGPT runs. They go through OpenAI's API with web search switched on, using the model each release names in its engine roster: gpt-4.1-mini-2025-04-14 in current releases, while earlier runs in the window were answered by gpt-4o-mini-search-preview-2025-03-11. That is the retrieval layer apps and research agents built on OpenAI's API use. The signed-in ChatGPT app answers with its own models and search pipeline and cites differently: a preprint submitted on 2026-10-11 and not yet peer reviewed found that Google Search and OpenAI's API on comparable models together recovered about half of the hostnames ChatGPT Web cited (48.7 and 50.3 percent on two model settings) and 26 to 28 percent of its exact URLs (arXiv 2610.15382v1). Claude, Gemini and Perplexity runs are likewise API runs with web search, on the models the roster names.

Method note, 2026-09-25. From that date, Google AI Mode and Google AI Overviews runs come through a different collection path than earlier runs, with no overlapping days, and answers collected on the two paths differ in how many distinct domains each cites. Per-answer figures for those two engines are read within one side of 2026-09-25, not as a trend across it.

Largest week-over-week movers among graded domains #

Of the 878 domains graded A, B or C in both releases, these rates moved most. Change is the difference between the two published cumulative rates, in percentage points. It records that a rate moved, not why: in the same week the basket went from 1,227 to 1,255 eligible questions and observed runs from 27,776 to 31,629, so a moved rate can reflect what was asked as much as how engines cite.

Rates that rose #

Rates that fell #

Segment leaders that changed #

A leader is the graded domain outside the publisher's related parties with the highest citation rate in the segment, on the segment's own denominator; domains tied on rate are listed together.

Segments that crossed the evidence floor #

Segment leaders by category #

The leader of every published segment, with its citation rate on that segment's runs. "Collecting" segments have not yet cleared the evidence floor of 10 runs across 7 run dates and carry no leader.

Do the cited sources support the answer? #

Answer-Source Fidelity is a separate measurement of claim support, not citation frequency. This edition preserves the published Fidelity snapshot generated 2026-10-25T11:35:14.651Z; it is not a week-only rate and may cover a different observation period from the Index.

Legacy baseline — frozen corpus, grade-time fetch basis #

Semantic cohort: c74383df31771cfe. Cohorts with different measurement semantics are not pooled.

• ChatGPT (reported): Of the 1255 resolvable citations for this engine, 54.8% were Supported; resolvable coverage was 77% (1255/1630).
• Claude (collecting): Engine still COLLECTING: only 88 of 1361 citations were resolvable (coverage 6.5%) — below the evidence floor, so no fidelity rate is reported.
• Gemini (collecting): Engine still COLLECTING: only 392 of 4349 citations were resolvable (coverage 9%) — below the evidence floor, so no fidelity rate is reported.
• Perplexity (reported): Of the 1298 resolvable citations for this engine, 50.1% were Supported; resolvable coverage was 47.6% (1298/2726).

Collection-time series — snapshot basis, bounded snapshot retry + deferral (F4-3) #

Semantic cohort: 06ddb22c15fa05d0. Cohorts with different measurement semantics are not pooled.

• ChatGPT (reported): Of the 12128 resolvable citations for this engine, 53.2% were Supported; resolvable coverage was 76.6% (12128/15837).
• Claude (collecting): Engine still COLLECTING: only 0 of 0 citations were resolvable (coverage 0%) — below the evidence floor, so no fidelity rate is reported.
• Gemini (collecting): Engine still COLLECTING: only 0 of 0 citations were resolvable (coverage 0%) — below the evidence floor, so no fidelity rate is reported.
• Perplexity (collecting): Engine still COLLECTING: only 0 of 0 citations were resolvable (coverage 0%) — below the evidence floor, so no fidelity rate is reported.

Collection-time series — snapshot basis, bounded snapshot retry + deferral (F4-3), 12.5% random sample of every engine's citations #

Semantic cohort: 36357120b9cc2a56. Cohorts with different measurement semantics are not pooled.

• ChatGPT (reported): Of the 327 resolvable citations in a 12.5% random sample of this engine's citations, 57.2% were Supported (±5 pts, 95%); resolvable coverage was 83.8% (327/390 sampled, ±3.4 pts).
• Claude (collecting): Still COLLECTING: only 23 of 387 citations in a 12.5% random sample of this engine's citations were resolvable (coverage 5.9% ±2.2 pts) — below the evidence floor, so no fidelity rate is reported.
• Gemini (collecting): Still COLLECTING: only 6 of 51 citations in a 12.5% random sample of this engine's citations were resolvable (coverage 11.8% ±8.3 pts) — below the evidence floor, so no fidelity rate is reported.
• Perplexity (reported): Of the 413 resolvable citations in a 12.5% random sample of this engine's citations, 48.2% were Supported (±4.5 pts, 95%); resolvable coverage was 46.1% (413/896 sampled, ±3.1 pts).

Published dataset SHA-256: 424e11005fbe6db314e02193fcec70de575bc4bab8cd6ee33c6bfb922b46cf97. Current measurement and method · Current dataset. The linked dataset advances; the snapshot above stays fixed with this edition.

How this report is built #

• Source: Machine Relations Index release mri_score_v2.1+2026-10-26+36825d1675fa (methodology mri_score_v2.1, window 2026-05-10 to 2026-10-26), compared with mri_score_v2.1+2026-10-19+da0ee4378219. The current release is public at machinerelations.ai/data/machine-relations-index.json; figures for the earlier release are read from the same file as committed on 2026-10-19.
• Rates are cumulative over the observation window, not rates for the week alone. Week-over-week change compares two published rates and is never read as a cause.
• Only segments the release publishes, at 10 or more observed runs across 7 or more run dates, are reported. Only domains with a confidence tier (A, B or C) are ranked or listed as movers; tiers are the Index's own.
• Domains operated by the publisher of this site or its related parties (authoritytech.io, machinerelations.ai, jaxonparrott.com, christianlehman.com, presspool.ai, paralabs.ai, paralax.ai) are left out of every ranking in this report. Their Index profiles remain public.
• The method is set out at machinerelations.ai/index, and known data issues and corrections are logged in the Index methodology and update log. Corrections to an edition are made there and in the edition.

FAQ #

What is the Machine Relations Index Report? A weekly reading of the daily public release of the Machine Relations Index: the most-cited sources, the largest movers among graded domains and the leader of every published segment, each figure tied to a release id and linked to the Index page that publishes it.

Does a first place mean a source is better? No. It means answer engines cited it most often for that question shape in that category during the window. The Index measures citation, not accuracy; whether a cited source supports the answer is a separate measurement.

Why can a rate fall while a source gains citations? A rate is citations over observed runs. reddit.com was cited in 2,550 runs this week against 2,478 a week earlier, while observed runs grew to 31,629; the rate moves with both.

Cite this edition #

Machine Relations Index (MRI) by Jaxon Parrott, Machine Relations Research — machinerelations.ai. alibaba.com replaces reddit.com as the most-cited graded source in Consumer Products / Is it worth it, at 19.76%. Release mri_score_v2.1+2026-10-26+36825d1675fa. https://machinerelations.ai/research/machine-relations-index-report-2026-10-26. CC BY 4.0.

APA

Parrott, J. (2026). Machine Relations Index Report, October 26, 2026: alibaba.com replaces reddit.com as the most-cited graded source in Consumer Products / Is it worth it, at 19.76% (Version mri_score_v2.1+2026-10-26+36825d1675fa) [Data set]. Machine Relations Research. https://machinerelations.ai/research/machine-relations-index-report-2026-10-26

BibTeX

@misc{parrott2026mrimachinerelationsindexreport20261026,
  author = {Parrott, Jaxon},
  title = {Machine Relations Index Report, October 26, 2026: alibaba.com replaces reddit.com as the most-cited graded source in Consumer Products / Is it worth it, at 19.76\%},
  year = {2026},
  version = {mri\_score\_v2.1+2026-10-26+36825d1675fa},
  publisher = {Machine Relations Research},
  url = {https://machinerelations.ai/research/machine-relations-index-report-2026-10-26},
  license = {CC-BY-4.0},
  note = {Machine Relations Index (MRI) by Jaxon Parrott, Machine Relations Research — machinerelations.ai}
}

Citation file: https://machinerelations.ai/CITATION.cff