Datasets:
Data Processing Documentation
Dataset: StakeBench — Evaluating Language Understanding Grounded in Market Commitment (working name during collection: PolySent)
Updated: 2026-10-27 (v1.1: §6 now points to the released raw files and scripts; collection documentation unchanged since 2026-03-18)
Platforms: Polymarket (polymarket_data/) · Manifold Markets (manifold_data/)
Table of Contents
- Overview
- Polymarket Dataset
- Manifold Dataset
- Schema Comparison
- Descriptive Statistics
- Raw Files and Scripts
1. Overview
| Polymarket | Manifold | |
|---|---|---|
| Market type | Real-money binary/multi-outcome prediction markets | Virtual-currency (Mana) binary prediction markets |
| API | gamma-api.polymarket.com + data-api.polymarket.com |
api.manifold.markets/v0 |
| Market filter (collection) | Event-level: total volume ≥ $10,000 USD + comments ≥ 100 | Market-level: volume ≥ 10,000 M$ + bettors ≥ 50 + has comments |
| Comment filter (collection) | ≥ 3 chars; ≥ 10 per market | ≥ 3 chars; ≥ 10 per market; within market lifecycle |
| Comment filter (cleaning) | Markets with < 10 comments removed; empty questions removed | Markets with < 100 comments removed; empty questions removed |
| Cleaned comments | 514,314 | 46,562 |
| Cleaned markets | 2,070 | 191 |
| Unique users | 24,909 | 3,250 |
| Date range | 2024-05-02 → 2026-03-12 | 2022-01-14 → 2026-03-07 |
2. Polymarket Dataset
2.1 Topic Collection
Script: get_polymarket_topics.py
Output: polysent_data/valid_topics.jsonl, polysent_data/valid_topics_summary.csv
Pipeline
GET gamma-api.polymarket.com/markets
└─ params: closed=True, limit=500, offset=0..N
└─ paginate until empty response (≤ MAX_PAGES=2000, ~1M markets)
└─ per market: extract event_id, volume, comment_count
└─ aggregate by event_id:
total_volume = Σ volume across all markets in the event
comment_count = event-level commentCount (shared)
best_market = highest-volume market (representative)
└─ filter: total_volume ≥ $10,000 AND comment_count ≥ 100
└─ classify category by keyword matching (crypto/politics/economics/sports/technology)
Key Parameters
| Parameter | Value | Description |
|---|---|---|
MIN_TOTAL_VOLUME |
10,000 | Minimum USD trading volume per event |
MIN_COMMENT_COUNT |
100 | Minimum comments per event |
PAGE_LIMIT |
500 | Markets per API request |
SLEEP |
0.15 s | Inter-request delay |
Category Classification
Keywords are matched against the representative market's question text (case-insensitive substring match). The category with the most keyword hits wins; no match → "other".
Categories: crypto, politics, economics, sports, technology, other
2.2 Comment Collection
Script: get_polymarket_comments.py
Input: polysent_data/valid_topics_summary.csv (column best_market_id)
Output: polysent_data/comments.csv
Pipeline
For each target market_id:
1. GET gamma-api.polymarket.com/comments
└─ params: parent_entity_type=market, parent_entity_id=<id>
└─ fallback: Event → Series (auto-detected)
└─ paginate with offset until exhausted
2. For each commenter's user_address:
GET data-api.polymarket.com/activity
└─ parallel fetch (8 threads, ThreadPoolExecutor)
└─ reconstruct historical position at comment creation time:
position_side = Yes / No / <team> (market-specific)
position_size = USD net cost (Σ BUY − Σ SELL; can be negative when profitable)
position_shares = net shares held
3. Write rows to comments.csv (append / resumable via progress.json)
Anti-Ban Measures
- Random User-Agent rotation (5 browser strings)
- Exponential backoff + jitter on HTTP 429/5xx (max 120 s)
- Optional proxy pool rotation (
proxies.txt) - Inter-request jitter sleep:
BASE_SLEEP ± JITTER = 0.12 ± 0.08 s - Resume support:
progress.jsontracksdone / skipped / failedper market
Collection Filters
| Filter | Value | Note |
|---|---|---|
MIN_COMMENT_LENGTH |
3 chars | Loose; stricter post-hoc filter recommended (>20) |
MIN_COMMENTS_PER_MARKET |
10 | Markets below this are marked skipped |
| Time window | [market_start_time, market_end_time] |
Comments outside market lifecycle dropped |
Output Schema (raw comments.csv)
| Field | Type | Description |
|---|---|---|
market_id |
str | Polymarket market ID |
slug |
str | URL slug |
question |
str | Market question |
condition_id |
str | On-chain condition ID |
category_validated |
str | Keyword-classified category (5 classes) |
market_start_time |
ISO8601 | Market open time |
market_end_time |
ISO8601 | Market close/settlement time |
parent_entity_type_used |
str | Event or Series (fallback tracking) |
parent_entity_id_used |
str | Entity ID used for comment API call |
comment_id |
str | Unique comment ID (may repeat across markets sharing a Series) |
created_at |
ISO8601 | Comment timestamp (UTC) |
text |
str | Comment body |
pseudonym |
str | Anonymized display name |
user_address |
str | On-chain ETH wallet address |
proxy_wallet |
str | Polymarket proxy wallet |
position_side |
str | Yes / No / team name at comment time |
position_size |
float | USD net cost (can be negative when profitable) |
position_shares |
float | Net shares held at comment time |
reactions |
JSON str | Raw reaction array |
reaction_count |
int | Total reactions (occasional −1 from API bug) |
report_count |
int | Number of reports |
parent_comment_id |
str | Parent comment ID (NaN for top-level) |
reply_count |
int | Replies received (within collection window) |
Note on
comment_idduplicates: Markets sharing a Polymarket Series pool share the same comment thread. The script collects comments for each market with its own time window, so the samecomment_idmay appear with differentmarket_idvalues. Deduplicate bycomment_idfor unique-comment analysis.
2.3 Cleaning
Script: polymarket_data/clean_comments.py
| Step | Operation | Effect |
|---|---|---|
| 1 | Drop category column |
100% missing (Gamma API does not expose this field) |
| 2 | Strip whitespace from question; remove markets where question is empty/"nan" |
Data integrity |
| 3 | Remove markets with < 10 valid comments | Minimum discussion threshold |
| 4 | Reorder columns to reference schema order | Consistency |
Run summary (from run.log):
- Input: 2,469 markets from
valid_topics_summary.csv - Completed: 2,070 / Skipped: 399 / Failed: 0
- Runtime: ~9.7 hours
3. Manifold Dataset
3.1 Topic Collection
Script: get_manifold_topics.py
Output: manifold_data/valid_markets.jsonl, manifold_data/valid_markets_summary.csv
Pipeline
GET api.manifold.markets/v0/search-markets
└─ params: filter=resolved, contractType=BINARY, sort=liquidity
└─ paginate with offset (100 per page, up to MAX_PAGES=5000)
└─ per market apply filters:
volume ≥ 10,000 M$ (Mana)
bettors ≥ 50
lastCommentTime is not None
└─ classify category by keyword matching (same keyword dict as Polymarket)
└─ NOTE: comment-count filter deferred to cleaning step
Key Parameters
| Parameter | Value | Description |
|---|---|---|
MIN_VOLUME_MANA |
10,000 | Minimum Mana (M$) trading volume |
MIN_BETTORS |
50 | Minimum unique bettors |
PAGE_LIMIT |
100 | Markets per API request |
BASE_SLEEP |
0.15 s | Inter-request delay (Manifold limit: 500 req/min) |
Currency note: Manifold uses virtual currency Mana (M$), not real USD.
volumeandposition_sizeare not directly comparable to Polymarket figures.
3.2 Comment Collection
Script: get_manifold_comments.py
Input: manifold_data/valid_markets.jsonl
Output: manifold_data/comments.csv
Pipeline
For each market (resolution = YES or NO only):
1. GET api.manifold.markets/v0/comments
└─ params: contractId=<id>, limit=1000
└─ cursor-based pagination (before=<last_id>)
└─ extract plain text from ProseMirror JSON (recursive content node walk)
└─ filter: created_at ∈ [market.created_time, market.resolution_time]
2. For each unique commenter's userId (parallel, 8 threads):
GET /v0/bets?contractId=<id>&userId=<uid>
└─ cursor-based pagination
└─ reconstruct position at comment time:
net_mana[YES] = Σ amount for YES bets before comment_ts
net_mana[NO] = Σ amount for NO bets before comment_ts
position_side = dominant side (or None if both ≤ 0)
└─ prob_at_comment = probAfter of last bet before comment_ts
3. Append rows to comments.csv (resumable via progress.json)
Key Differences from Polymarket
| Aspect | Polymarket | Manifold |
|---|---|---|
| Position currency | USD (real money) | Mana (virtual currency) |
| Position source | Dedicated activity API per user | Bet records reconstructed per user |
| Market probability | Dedicated /prices-history endpoint |
Interpolated from probAfter in bet records |
| Text format | Plain text | ProseMirror JSON → recursively extracted |
| Reply count | Provided by API | Not in API; back-calculated from replyToCommentId |
| Resolution ground truth | Not in API | YES / NO in market metadata |
Collection Filters
| Filter | Value |
|---|---|
MIN_COMMENT_LENGTH |
3 chars |
MIN_COMMENTS_PER_MARKET |
10 |
| Resolution filter | Only YES / NO markets (excludes MKT, CANCEL, N/A) |
| Lifecycle filter | Comments outside [created_time, resolution_time] dropped |
Output Schema (raw comments.csv)
| Field | Type | Description |
|---|---|---|
market_id |
str | Manifold market ID |
slug |
str | URL slug |
question |
str | Market question |
outcome_type |
str | Always BINARY |
category |
str | Keyword-classified category |
resolution |
str | YES / NO (ground truth) |
comment_id |
str | Unique comment ID |
created_at |
ISO8601 | Comment timestamp (UTC, ms precision) |
text |
str | Extracted plain text |
user_id |
str | Manifold user ID |
user_name |
str | Username |
position_side |
str | YES / NO / empty |
position_mana |
float | Net Mana invested at comment time |
position_shares |
float | Net shares held at comment time |
prob_at_comment |
float | Market probability snapshot at comment time |
likes |
int | Like count |
parent_comment_id |
str | Parent comment ID (NaN for top-level) |
reply_count |
str | Empty (back-calculated during cleaning) |
3.3 Cleaning
Script: manifold_data/clean_comments.py
| Step | Operation | Effect |
|---|---|---|
| 1 | Back-calculate reply_count from parent_comment_id value counts |
API does not provide reply_count |
| 2 | Rename columns to align with Polymarket schema | user_id→user_address, user_name→pseudonym, position_mana→position_size, likes→reaction_count |
| 3 | Drop markets where question is empty/"nan" |
Data integrity |
| 4 | Remove markets with < 100 valid comments | Ensures sufficient discussion depth per market for NLP tasks |
| 5 | Reorder columns (retain Manifold-specific fields: outcome_type, resolution, prob_at_comment) |
Schema alignment |
Threshold change: The minimum comments per market was raised from 10 to 100 to retain only well-discussed markets with sufficient context for sentiment analysis. This reduces market count from ~2,926 to 191 but increases average comment depth from 21 to 163 per market.
4. Schema Comparison
| Field | Polymarket | Manifold | Notes |
|---|---|---|---|
market_id |
✓ | ✓ | Different ID systems (numeric vs. alphanumeric) |
slug |
✓ | ✓ | |
question |
✓ | ✓ | |
condition_id |
✓ | — | On-chain condition (Polymarket only) |
outcome_type |
— | ✓ | Always BINARY (Manifold only) |
category_validated / category |
✓ | ✓ | Same keyword logic; different field names |
resolution |
— | ✓ | YES/NO ground truth (Manifold only) |
market_start_time |
✓ | — | |
market_end_time |
✓ | — | |
parent_entity_type_used |
✓ | — | API fallback tracking (Polymarket only) |
comment_id |
✓ (may repeat) | ✓ (unique) | |
created_at |
✓ | ✓ | ISO8601 UTC |
text |
✓ | ✓ | |
pseudonym |
✓ | ✓ | (renamed from user_name) |
user_address |
✓ | ✓ | (renamed from user_id) |
proxy_wallet |
✓ | — | Polymarket on-chain proxy |
position_side |
Yes/No/team | YES/NO | Format differs; Polymarket has 73 distinct values |
position_size |
USD (can be negative) | Mana M$ | Not directly comparable |
position_shares |
✓ | ✓ | |
prob_at_comment |
— | ✓ | Market probability snapshot (Manifold only) |
reactions |
JSON str | — | Raw reactions (Polymarket only) |
reaction_count |
✓ | ✓ | (renamed from likes); Polymarket occasionally −1 |
report_count |
✓ | — | |
parent_comment_id |
✓ | ✓ | |
reply_count |
✓ | ✓ | Back-calculated for Manifold |
5. Descriptive Statistics
Analysis scripts:
data/analysis/descriptive_stats.pyanddata/analysis/plot_stats.pyRun fromdata/directory:python analysis/descriptive_stats.py
5.1 Basic Scale
| Metric | Polymarket | Manifold |
|---|---|---|
| Total comments (cleaned) | 514,314 | 46,562 |
Unique comment_id (deduplicated) |
266,446 | 46,562 |
| Unique markets | 2,070 | 191 |
| Unique users | 24,909 | 3,250 |
| Fields per row | 23 | 18 |
| Date range | 2024-05-02 → 2026-03-12 | 2022-01-14 → 2026-03-07 |
| Time span | ~22 months | ~50 months |
Polymarket duplicate rows: 48.2% of rows share a
comment_idwith another row (same comment collected under differentmarket_idfor markets sharing a Series comment pool). Deduplicate withdf.drop_duplicates(subset='comment_id', keep='first')before unique-comment analyses.
5.2 Market Coverage
Comments per Market
| Statistic | Polymarket | Manifold |
|---|---|---|
| Count (markets) | 2,070 | 191 |
| Mean | 248.5 | 243.8 |
| Std | 1,284.1 | 197.1 |
| Min | 10 | 100 |
| 25th pct | 41 | 126 |
| Median | 70 | 163 |
| 75th pct | 127 | 275 |
| Max | 25,049 | 990 |
Market Depth Brackets (Polymarket)
| Threshold | Markets | Share |
|---|---|---|
| ≥ 10 comments | 2,070 | 100% |
| ≥ 50 comments | 1,363 | 65.8% |
| ≥ 100 comments | 692 | 33.4% |
| ≥ 200 comments | 259 | 12.5% |
Top 10 Markets by Comment Count
Polymarket:
| Rank | Market ID | Comments | Question |
|---|---|---|---|
| 1 | 519075 | 25,049 | Will Hunor Kelemen win the Romanian presidential election? |
| 2 | 516767 | 22,444 | Will Pierre Poilievre be the next Canadian Prime Minister? |
| 3 | 514139 | 19,284 | Will Rafał Trzaskowski be the next President of Poland? |
| 4 | 253591 | 17,034 | Will Donald Trump win the 2024 US Presidential Election? |
| 5 | 546814 | 16,326 | Will Zelenskyy wear a suit before July? |
| 6 | 506968 | 14,810 | Will Israel invade Syria in 2024? |
| 7 | 507276 | 12,949 | TikTok banned in the US before May 2025? |
| 8 | 532741 | 11,074 | US military action against Iran before July? |
| 9 | 551650 | 11,037 | US military action against Iran before August? |
| 10 | 552650 | 9,331 | Fordow nuclear facility destroyed before July? |
Manifold:
| Rank | Market ID | Comments | Question |
|---|---|---|---|
| 1 | l2Pci4rwD2S50eFGZiCj | 990 | Is the probability of dying in the Snake Eyes Paradox 1/36? |
| 2 | 1sfbjcTu6zgqjCVjqWA2 | 961 | Will LK-99 room-temperature superconductivity be confirmed? |
| 3 | 7RZ7CnNVPKOGSh3v5pnn | 933 | Will @firstuserhere walk 100,000 steps in a day before 2023? |
| 4 | d1t4k3nz3t | 927 | Will Trump win the 2024 Election? |
| 5 | gPA029Rcyh | 919 | Will Manifold solve my puzzle? |
| 6 | YTIuuSsNRn2OlA4KykRM | 918 | Will Biden be the 2024 Democratic Nominee? |
| 7 | U3zLgOZkGUE7cvG98961 | 891 | Whales vs. Minnows: Will traders hold at least 10000x as many shares? |
| 8 | 0EVOQyEBz624ooYpOCfc | 844 | Hamas command center under al-Shifa Hospital? |
| 9 | PXd5l5qBVArJrSYZhivM | 808 | Will Tumbles be late to pay back a loan? |
| 10 | NRLwgQYqCLk5zTasmxOn | 762 | Will the average percentage of this market be above 50%? |
Polymarket: parent_entity_type Distribution
| Type | Comments | Share |
|---|---|---|
| Series | 323,082 | 62.8% |
| Event | 191,232 | 37.2% |
Series markets (comment pool shared across multiple related markets) account for 62.8% of all rows and are the primary source of comment_id duplication.
5.3 Comment Text Analysis
Text Length (characters)
| Statistic | Polymarket | Manifold |
|---|---|---|
| Mean | 69.4 | 208.5 |
| Std | 87.9 | 347.5 |
| Min | 2 | 3 |
| 25th pct | 22 | 49 |
| Median | 44 | 107 |
| 75th pct | 85 | 230 |
| 90th pct | ~160 | ~470 |
| Max | 1,492 | 9,132 |
Manifold comments are ~2.4× longer on average (median 107 vs. 44 chars). This reflects Manifold's community culture of extended argumentative discussion, compared to Polymarket's shorter reaction-style comments.
Text Length Brackets
| Bracket | Polymarket | Manifold |
|---|---|---|
| < 20 chars | ~124,000 (24.1%) | ~5,600 (12.0%) |
| 20–100 chars | ~243,000 (47.3%) | ~14,900 (32.0%) |
| > 100 chars | ~147,000 (28.6%) | ~26,100 (56.1%) |
Polymarket
MIN_COMMENT_LENGTH=3(not the Guide-recommended 20). For downstream tasks requiring substantive text, applylen(text) > 20post-hoc filter.
5.4 Position (Stake) Data
Position data links each comment to the commenter's financial stake at the time of writing — a key feature for the Polymarket Sentiment Analysis (PSA) task.
Coverage Summary
| Metric | Polymarket | Manifold |
|---|---|---|
Comments with position_side |
155,205 (30.2%) | 37,497 (80.5%) |
Comments with position_size > 0 |
139,848 (27.2%) | 37,430 (80.4%) |
Comments with position_size < 0 |
15,336 (3.0%) | 0 |
| No position (NaN) | 359,109 (69.8%) | 9,065 (19.5%) |
Manifold's much higher position coverage (80.5%) reflects the fact that Manifold users generally bet before commenting, whereas many Polymarket users comment without holding a position. The >= 100 market filter further concentrates well-engaged markets.
Position Side Distribution
| Value | Polymarket | Polymarket % | Manifold | Manifold % |
|---|---|---|---|---|
| Yes / YES | 77,062 | 15.0% | 19,258 | 41.4% |
| No / NO | 63,760 | 12.4% | 18,239 | 39.2% |
| Team / other names | ~14,383 | 2.8% | — | — |
| No position (NaN) | 359,109 | 69.8% | 9,065 | 19.5% |
Polymarket position_side has 73 distinct values: Yes/No (90.8% of positioned comments), Up/Down (crypto markets), and team names (NBA/MLB sports markets).
Position Size Distribution (comments with size > 0)
| Statistic | Polymarket (USD) | Manifold (Mana M$) |
|---|---|---|
| Count | 139,848 | 37,430 |
| Mean | $3,164 | M$24,408 |
| Std | $22,472 | M$182,496 |
| 25th pct | $45.7 | M$123 |
| Median | $242 | M$949 |
| 75th pct | $1,174 | M$6,000 |
| Max | $2,956,218 | M$4,404,784 |
Polymarket
position_size < 0(15,336 rows): Legitimate data — occurs when a user's total SELL proceeds exceed BUY costs (i.e., trading profit; the user remains in a net-long position asposition_shares > 0). Do not remove; addis_profit_stateflag for downstream handling.
Position Size Tier Breakdown (Polymarket, > 0 only)
| Tier | Range (USD) | Count | % of positioned |
|---|---|---|---|
| Retail | < $100 | 52,259 | 37.4% |
| Small | $100–$500 | 35,042 | 25.1% |
| Medium | $500–$1,000 | 14,162 | 10.1% |
| Large | $1,000–$5,000 | 23,865 | 17.1% |
| XLarge | $5,000–$10,000 | 6,315 | 4.5% |
| Whale | $10,000–$50,000 | 6,732 | 4.8% |
| Mega | > $50,000 | 1,473 | 1.1% |
Position Size Tier Breakdown (Manifold, > 0 only)
| Tier | Range (M$) | Count | % of positioned |
|---|---|---|---|
| Retail | < M$100 | 8,621 | 23.0% |
| Small | M$100–500 | 7,191 | 19.2% |
| Medium | M$500–1,000 | 3,480 | 9.3% |
| Large | M$1,000–5,000 | 7,981 | 21.3% |
| XLarge | M$5,000–10,000 | 3,008 | 8.0% |
| Whale | M$10,000–50,000 | 4,944 | 13.2% |
| Mega | > M$50,000 | 2,205 | 5.9% |
5.5 Reply Structure
| Metric | Polymarket | Manifold |
|---|---|---|
Is a reply (has parent_comment_id) |
259,226 (50.4%) | 33,020 (70.9%) |
Has received replies (reply_count > 0) |
101,081 (19.7%) | 7,217 (15.5%) |
reply_count mean |
0.46 | 0.55 |
reply_count max |
152 | 78 |
Manifold's very high reply rate (70.9%) reflects its forum-style discussion culture. Note that
reply_countis locally computed (within the collection window), not the API's authoritative total.
5.6 Engagement (Reactions/Likes)
| Metric | Polymarket (reaction_count) |
Manifold (reaction_count / likes) |
|---|---|---|
| Mean | 1.06 | 1.72 |
| Median | 0 | 1 |
| 75th pct | 1 | 2 |
| Max | 160 | 81 |
| With ≥ 1 reaction | 230,329 (44.8%) | — |
| With ≥ 5 reactions | 26,329 (5.1%) | — |
reaction_count = −1 (API anomaly) |
42 | 0 |
Polymarket
reaction_count = −1(42 rows) is an API-side bug; replace with 0 during downstream cleaning.
5.7 User Behavior
Activity Distribution
| Statistic | Polymarket | Manifold |
|---|---|---|
| Unique users | 24,909 | 3,250 |
| Mean comments/user | 20.6 | 14.3 |
| Median comments/user | 3 | 2 |
| 75th pct | 10 | 9 |
| Max | 6,054 | 1,194 |
Both platforms show a long-tail distribution. The most active Polymarket user posted 6,054 comments (vs. 279,347 in the earlier v0312 dataset), indicating the v2 collection script substantially reduced bot-like behavior.
Top 5 Most Active Users
Polymarket (by ETH address prefix):
| Rank | user_address | Comments |
|---|---|---|
| 1 | 0x6e26a51e... | 6,054 |
| 2 | 0x5cc591f9... | 5,844 |
| 3 | 0xf3a34b19... | 4,748 |
| 4 | 0x238b427f... | 4,664 |
| 5 | 0x4711c314... | 4,473 |
Manifold (by user ID prefix):
| Rank | user_address | Comments |
|---|---|---|
| 1 | 4JuXgDx47x... | 1,194 |
| 2 | y1hb6k7txd... | 762 |
| 3 | zgCIqq8AmR... | 757 |
| 4 | sCOvPc5J2s... | 698 |
| 5 | uIA81X2m3a... | 653 |
5.8 Temporal Distribution
Monthly Comment Volume
Polymarket (2024-05 to 2026-03):
| Month | Comments | Note |
|---|---|---|
| 2024-05 | 9 | Platform cold-start |
| 2024-08 | 372 | |
| 2024-10 | 9,485 | Pre-election ramp-up |
| 2024-11 | 25,143 | US election |
| 2024-12 | 48,980 | Post-election activity |
| 2025-01 | 46,020 | |
| 2025-04 | 43,632 | |
| 2025-06 | 123,040 | Peak (Iran/nuclear crisis markets) |
| 2025-07 | 53,050 | |
| 2025-08 | 15,425 | |
| 2025-11 | 407 | Sharp drop in market activity |
| 2025-12 | 6,739 | |
| 2026-01–03 | ~224 | Tail (incomplete months) |
Manifold (2022-01 to 2026-03):
| Period | Comments | Note |
|---|---|---|
| 2022-01–10 | < 500/month | Early platform growth |
| 2022-11 | 1,165 | Growth inflection |
| 2023-01–12 | 1,350–3,089/month | Steady growth phase |
| 2023-12 | 3,089 | Peak year for 2023 |
| 2024-07 | 2,603 | Election season |
| 2024-11 | 1,456 | US election |
| 2025-05 | 1,575 | |
| 2026-01–03 | 654–102 | Recent (within-collection) |
5.9 Category Distribution
Polymarket
| Category | Comments | Share (of all) | Share (deduplicated) |
|---|---|---|---|
| politics | 99,858 | 19.4% | 36.3% |
| crypto | 50,508 | 9.8% | 9.0% |
| economics | 13,486 | 2.6% | 2.8% |
| sports | 5,500 | 1.1% | 0.4% |
| NaN / other | 345,062 | 67.1% | 51.6% |
category_validatedis keyword-matched; 67.1% of rows (51.6% deduplicated) fall outside the five defined categories. The high NaN rate reflects question phrasings that don't match any keyword.
Manifold
| Category | Comments | Share |
|---|---|---|
| other | 30,875 | 66.3% |
| politics | 6,252 | 13.4% |
| technology | 3,759 | 8.1% |
| crypto | 3,758 | 8.1% |
| sports | 1,174 | 2.5% |
| economics | 744 | 1.6% |
Manifold category is assigned at collection time; other dominates because many Manifold questions are platform-community or science/culture topics not covered by the five keyword sets.
5.10 Manifold-Specific: Resolution & Probability
Market Resolution
| Resolution | Comments | Share |
|---|---|---|
| YES | 25,009 | 53.7% |
| NO | 21,553 | 46.3% |
A near-balanced YES/NO split avoids class imbalance issues for binary prediction tasks.
Market Probability at Comment Time (prob_at_comment)
| Metric | Value |
|---|---|
| Coverage | 40,914 / 46,562 (87.9%) |
| Mean | 0.506 |
| Median | ~0.5 |
| Std | — |
The mean probability of ~0.5 indicates comments are distributed across the full lifecycle of markets, not concentrated near resolution (when probability collapses to 0 or 1).
5.11 Cross-Platform Comparison
| Metric | Polymarket | Manifold |
|---|---|---|
| Total comments | 514,314 | 46,562 |
| Unique markets | 2,070 | 191 |
| Unique users | 24,909 | 3,250 |
| Median text length | 44 chars | 107 chars |
| Median comments/market | 70 | 163 |
| Position coverage | 30.2% | 80.5% |
| Reply rate (has parent) | 50.4% | 70.9% |
| Reaction mean | 1.06 | 1.72 |
| Ground-truth resolution | ✗ | ✓ |
| Market probability | ✗ | ✓ (87.9% coverage) |
| Currency | Real USD | Virtual Mana |
Key trade-offs:
- Polymarket: larger scale (11× more comments, 11× more markets), real financial stakes, but lower position coverage and no built-in resolution ground truth.
- Manifold: smaller but higher-depth markets (min 100 comments), near-complete position data (80.5%), resolution ground truth, and market probability snapshots; however, Mana is virtual currency, limiting financial signal interpretation.
6. Raw Files and Scripts
The raw outputs named in §2–§3 (valid_topics.jsonl, valid_markets.jsonl, comments.csv,
user_positions.csv) are released unmodified in the raw/ folder of this dataset; raw/README.md
gives their row counts, columns and the exact steps that produce the *_clean.csv files. The
collection scripts (get_*_topics.py, get_*_comments.py, get_*_position.py, get_*_data.py)
and the cleaning scripts (clean_comments.py, clean_positions.py) are in the code repository
under collection/: https://github.com/PEIYUNHUA/stakebench_code_NeurIPS26.
Note on the released polymarket/comments_clean.csv: it is GB18030-encoded and 32 rows shorter
than the raw crawl output; the raw file is UTF-8. See raw/README.md (Encoding note).
Generated: 2026-03-18