Pith Number
pith:APGJXPZL
pith:2022:APGJXPZLQ5Z7OUNWD2SFCWWLBO
not attested
not anchored
not stored
refs pending
Twitter Spam and False Accounts Prevalence, Detection and Characterization: A Survey
arxiv:2211.05913 v4 · 2022-11-10 · cs.SI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{APGJXPZLQ5Z7OUNWD2SFCWWLBO}
Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge
Record completeness
1
Bitcoin timestamp
2
Internet Archive
3
Author claim
· sign in to
claim
4
Citations
5
Replications
✓
Portable graph bundle live · download bundle · merged
state
The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same
current state with the deterministic merge algorithm.
Cited by
Receipt and verification
| First computed | 2026-07-05T06:02:01.788762Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
03cc9bbf2b8773f751b61ea4515acb0bae41f66cca93a38fb475d30c03439d08
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/APGJXPZLQ5Z7OUNWD2SFCWWLBO \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 03cc9bbf2b8773f751b61ea4515acb0bae41f66cca93a38fb475d30c03439d08
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "d10e015e4dcc66a38bd8f13540f07809bcf079b588f73507b027b5e8be8a38bc",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.SI",
"submitted_at": "2022-11-10T23:17:08Z",
"title_canon_sha256": "8f293af9d6864697874f539da2ad4ba39524a4c8c4b440eef5d5997379f8b04d"
},
"schema_version": "1.0",
"source": {
"id": "2211.05913",
"kind": "arxiv",
"version": 4
}
}