Pith Number

pith:4KDJZWCS

pith:2026:4KDJZWCSTUL5Z67TAY3QDLW26V

not attested not anchored not stored refs resolved

Linking Extreme Discourse to Structural Polarization in Signed Interaction Networks

Janet B. Pierrehumbert, Li Zhang, Tyler Bonnet, Xiaowen Dong, Zhijin Guo

LLM stance scores turn observed text into continuous signed edges that connect discourse intensity to temporal changes in structural polarization.

arxiv:2605.12814 v1 · 2026-05-12 · cs.SI · cs.CL

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\pithnumber{4KDJZWCSTUL5Z67TAY3QDLW26V}

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Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ 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.

Claims

C1strongest claim

Applying the framework to Reddit Brexit discussions, we analyze how window-level discourse signals, including toxicity, extreme scalar claims, and perplexity, relate to temporal variation in structural polarization. Edge-level and ablation analyses show that continuous, confidence-weighted signed edges reveal intensity-sensitive patterns that are muted under sign-only representations.

C2weakest assumption

That LLM stance scores provide accurate and unbiased continuous measures of agreement and disagreement in the observed text, allowing the derived signed edges to faithfully represent the underlying interaction structure without significant model-induced artifacts.

C3one line summary

A pipeline derives continuous signed edges from LLM stance scores on text and links discourse signals such as toxicity and extreme claims to changes in structural polarization measured by spectral and frustration scores on Reddit Brexit data.

References

53 extracted · 53 resolved · 0 Pith anchors

[1] Aho and Jeffrey D 1972

[2] Publications Manual , year = "1983", publisher = 1983

[3] Chandra and Dexter C 1981 · doi:10.1145/322234.322243

[4] Scalable training of

[5] Dan Gusfield , title =. 1997 1997

Receipt and verification

First computed	2026-05-18T03:09:12.356066Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

e2869cd8529d17dcfbf3063701aedaf57bcfc59199124acba4d7112080467367

Aliases

arxiv: 2605.12814 · arxiv_version: 2605.12814v1 · doi: 10.48550/arxiv.2605.12814 · pith_short_12: 4KDJZWCSTUL5 · pith_short_16: 4KDJZWCSTUL5Z67T · pith_short_8: 4KDJZWCS

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/4KDJZWCSTUL5Z67TAY3QDLW26V \
  | 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: e2869cd8529d17dcfbf3063701aedaf57bcfc59199124acba4d7112080467367

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "c23dedd0522a3660f8ef571f5bea60094d6140557cc36df5260ff083ba53894f",
    "cross_cats_sorted": [
      "cs.CL"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.SI",
    "submitted_at": "2026-05-12T23:14:37Z",
    "title_canon_sha256": "6e6d92eaea2035122f919fba5b69f7838dcb501d0665246ce0e7d5b1b19b22fb"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.12814",
    "kind": "arxiv",
    "version": 1
  }
}