The Reddit Market Index: how global Reddit talks about China tech & AI.
Reddit Market Index tracks how Reddit discusses China tech and AI: monthly net sentiment, brand share of voice, top communities and authors from 266,834 posts.
Data as of 2026-11-08cached snapshot
Posts analyzed
264,790
99.2% sentiment coverage
Communities profiled
945
subreddits with sentiment signals
Brands tracked
132
AI, tech & robotics brands
Authors profiled
165,676
influence + sentiment scored
Sentiment
Net Sentiment Index
MONTHLY · LAST 24 MONTHS
Monthly net sentiment score (NSS) across all monitored China-related discussion. NSS = (positive − negative) × 100 / total posts. Explore overall, per category, or per brand.
Monthly net sentiment trend: 2024-12 +14.0 to 2026-11 +7.0, 24 points.
Attention
Attention by Category
YEARLY · LAST 10 YEARS
Yearly discussion attention per keyword category, measured as the sum of Reddit post scores.
aipolicyrobottechgeoconsumer
Yearly attention by category, stacked sum of post scores: ai, policy, robot, tech, geo, consumer stacked over 10 dates from 2017 to 2026.
Sum of post scores. Absolute-volume metric — collection structure changed in 2026-03; cross-period levels are directional, not exact.
Attention
Brand Attention
MONTHLY · LAST 24 MONTHS
Monthly attention (sum of post scores) for the most-discussed brands in the selected category — switch between AI, Tech, and Robot. The top 7 brands are shown; all remaining brands are folded into Others.
Monthly AI brand attention, stacked sum of post scores: DeepSeek, Megvii, Alibaba, KIMI, Kuaishou, GLM, ByteDance, Others stacked over 24 dates from 2024-12 to 2026-11.
Brands
Brand Share of Voice
Score-weighted share of voice within the selected category's discussion — switch between AI, Tech, and Robot. Left: the category's monthly net sentiment trend. Right: brand SOV ranking for the category's latest data month.
2026-11 · MONTHLY
AI category monthly net sentiment trend: 2024-12 +21.9 to 2026-11 +25.0, 24 points.
#
Brand
SOV %
1
AlibabaNSS +20.8 · 649 posts
61.4%
2
DeepSeekNSS +42.6 · 340 posts
16.5%
3
KIMINSS +34.2 · 184 posts
9.0%
4
MiniMaxNSS +33.1 · 148 posts
6.4%
5
GLMNSS +28.9 · 97 posts
3.9%
6
ByteDanceNSS +27.4 · 157 posts
1.7%
7
KuaishouNSS +40.6 · 32 posts
0.6%
8
BaiduNSS -8.3 · 12 posts
0.2%
9
TencentNSS +20.7 · 29 posts
0.2%
10
ViduNSS +33.3 · 3 posts
0.0%
Sentiment
Brand Sentiment Split
ALL-TIME · 2008 → 2026-11-08
All-time sentiment composition for the top 15 brands by post volume in the selected category — switch between AI, Tech, and Robot.
NegativeNeutralPositive
All-time AI brand sentiment split
Name
Positive %
Neutral %
Negative %
DeepSeek
28
59
12
Alibaba
31
64
5
ByteDance
31
62
7
GLM
28
60
13
MiniMax
34
59
8
KIMI
30
58
12
Kuaishou
23
72
5
Baidu
15
75
10
Tencent
34
60
5
Vidu
7
91
2
Skywork
9
89
2
Megvii
3
93
4
Brands with ≥ 300 all-time posts in the category, top 15 by post count.
Hot posts
Hot Posts
TOP 10 BY SCORE · POOLED PER SLICE
One ranked list of what actually blew up: the top 10 posts by Reddit score within the selected slice. Filter by sentiment — Positive, Negative, or Neutral — by week, month, or all time, and by category and brand.
positive post“Yangwang U9X (BYD) have hit over 500 KM/h in Abu Dhabi highway top-speed run. German racing driver Marc Basseng achieved the speed during a…”🔥r/Damnthatsinteresting · 2026-11-0615,023
positive post“Convincingly three-dimensional chinese calligraphy that looks like it's floating in rural China”🔥r/nextfuckinglevel · 2026-11-0412,066
positive post“Official Statement: Qwen Models Will Stick to Open Source to the End!”🔥r/LocalLLaMA · 2026-11-025,120
positive post“Yangwang U9X (BYD) have hit over 500 KM/hr in Abu Dhabi highway top speed run. German racing driver Marc Basseng achieved the speed during a…”🔥r/nextfuckinglevel · 2026-11-063,285
positive post“Thank you for protecting us, great firewall”r/shitposting · 2026-11-072,681
positive post“Despite the challenges, this man is earning his living by delivering food on a three-wheeler. A beautiful example of determination and self-…”r/incredible_indians · 2026-11-032,059
positive post“‘It’s only when you see 49-ton trucks in China running on batteries that you realize how serious electrification is’: Octopus Energy CEO Gre…”r/europe · 2026-11-031,948
positive post“Giant enclosed membrane structures now cover large excavation zones on construction sites across China! They block over 95% of dust and cut…”r/thatsdamninteresting · 2026-11-031,861
positive post“Kimi-K3.1-Pro is now open-weights”r/LocalLLaMA · 2026-11-041,447
positive post“"Absolutely incredible: MIT researchers say GPT-6 Astra improved a small Qwen model’s math score from 7.9% to 48.1% by directly editing just…”r/accelerate · 2026-11-021,370
Pool tiers (score floors): weekly lists cover the collection era (since 2026-03) at score ≥ 30; monthly lists cover the last 24 months at score ≥ 100 — months since 2026-03 also draw on the score ≥ 30 collection-era pool; the all-time floor is score ≥ 300, with the two recent tiers layered on top. Neutral posts are included at the same floors. Pool keeps the top 10 per period for each sentiment, category, and brand; combined category × brand filters may surface fewer than 10, as may slices below a tier's floor. Weekly filtering before 2026-03 is deliberately not offered: per-week coverage before collection start is sparse backfill and would bias the lists. Absolute scores across 2026-03 carry the collection-structure change. Dates UTC.
Communities
Top Communities
ALL-TIME · 2008 → 2026-11-08
Where China-tech discussion concentrates. Filter by category or brand; rank by score, sentiment, subscribers, or post volume.
The most influential authors in China-tech discussion. Filter by category or brand; rank by score, volume, or sentiment.
#
Author
Total score
1
maxwellhill
476.1K
2
DoremusJessup
378.2K
3
ManiaforBeatles
343.7K
4
esberat
321.7K
5
c-k-q99903
285.4K
6
Wagamaga
272.3K
7
DaFunkJunkie
263.8K
8
elonmuskatemyson
263.2K
9
flyingcatwithhorns
247.9K
10
mczack13
241.5K
Pool: all-time top-100 authors per brand and per category by score.
Topics
Topic Matrix
ALL-TIME · 2008 → 2026-11-08
What the discussion is actually about. Word cloud: the most-discussed content tags (noise-filtered), sized by score, colored by net sentiment — hover for details. Table: core topic ranking.
Positive (NSS > +5)NeutralNegative (NSS < −5)
#
Topic
Total score
1
Geopolitics_and_Sanctions
20.9M
2
Hardware_and_Robotics
7.4M
3
Censorship_and_Safety
5.4M
4
Market_and_Macro_Economy
4.7M
5
Policy_and_Regulation
4.2M
6
Corporate_Strategy
3.5M
7
Model_Capabilities
1.9M
8
Tech_Comparison
1.8M
9
Data_Privacy
1.4M
10
UI_and_UX
820.8K
Use cases
Use Case Distribution
ALL-TIME · 2008 → 2026-11-08
What people actually use each brand for. Word cloud: use cases sized by post volume, colored by net sentiment — hover for details. Table: ranking by the selected metric.
Aggregated from view_usecase_distribution (use case × category × brand); NSS re-derived from summed pos/neg/post counts.
Full-history analysis by post publish date (2008 → data cutoff). Continuous collection runs since 2026-03; absolute-volume comparisons across 2026-03 carry a collection-structure change. Sub-30-post slices are suppressed as insufficient data. All timestamps UTC.
What the Reddit Market Index is
The Reddit Market Index condenses 266,834 Reddit posts about China tech and AI — spanning 945 profiled subreddits and 28 tracked brands — into monthly sentiment, attention, and share-of-voice series, plus community, author, topic, and use-case rankings drawn from 165,676 profiled authors. It exists to answer one question with data instead of anecdotes: how does global Reddit actually talk about China tech and AI, and how is that changing?
How to read the index
Two kinds of metrics appear on this page. Ratio metrics — net sentiment score (NSS), share of voice, and sentiment shares — are comparable across the full 2008-to-present history, because they divide out collection volume. Absolute-volume metrics — post counts and total scores — carry a collection-structure change in 2026-03, so cross-period volume comparisons are directional rather than exact; every chart built on absolute volumes says so in its footnote.
Methodology
Analysis covers the full post history by publish date, from 2008 to the latest data date shown in the "Data as of" badge.
NSS = (positive posts − negative posts) × 100 / total posts. Share of voice is score-weighted, not post-count-weighted. Any filter combination with fewer than 30 posts is suppressed as insufficient data rather than shown as an unstable percentage. Relative time windows are anchored to the latest data date, not to the current clock. All timestamps are UTC.
Data access
The dashboard is free to read and cite. The full dataset is not available for download; teams that need it can apply for API access, and brands can ask to be added to the tracking pool. Both go through one email.
When referencing the Reddit Market Index in articles, research, or reports, please cite it with the data cutoff date so readers know which snapshot you used:
KeepReal Reddit Market Index — China tech & AI on Reddit. Data as of 2026-11-08. https://keepreal.cc/data/reddit-market-index
TL;DR
One live index of China tech & AI discussion on Reddit: 266,834 posts across 945 subreddits, 132 brands, 165,676 profiled authors.
Ratio metrics (net sentiment, share of voice, sentiment shares) are comparable across the full 2008-to-present history; absolute volumes carry a 2026-03 collection change.
The dashboard is free to read and cite, with a visible data-cutoff date and a ready-to-paste citation; the full dataset is not downloadable, and API access is available on application.
FAQ
What is NSS (net sentiment score)?
NSS = (positive posts − negative posts) × 100 / total posts. It ranges from −100 to +100, and because it is a ratio rather than a volume, it stays comparable across the full monitoring history.
Why do absolute volumes shift around 2026-03?
Continuous collection started in 2026-03, which changed how many posts enter the corpus per period. Ratio metrics are unaffected; absolute post counts and scores across that boundary are directional, and affected charts are footnoted.
How fresh is the data?
Every module is stamped with a "Data as of" date equal to the latest post publish date in the corpus. The page refreshes its data assembly at most once every 24 hours; if a live refresh fails, the last good snapshot is served and labeled as a cached snapshot.
Can I download or cite the index?
Cite it freely: the citation block gives a ready-to-paste reference with the data-cutoff date. The full dataset is not available for free download; teams that need it can apply for API access at support@keepreal.cc. The underlying corpus of raw Reddit post text is not redistributed.