Pith Number

pith:D57XBBOV

pith:2026:D57XBBOV7Y2CGUOBI7BEHRRITW

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PERCEIVE: A Benchmark for Personalized Emotion and Communication Behavior Understanding on Social Media

Deyu Li, Jian Liao, Jianxing Zheng, Suge Wang, Yujin Zheng

PERCEIVE is the first benchmark to combine social media posts with readers' real comments, behavior, attributes and networks for personalized emotion analysis.

arxiv:2605.12525 v1 · 2026-04-10 · cs.SI · cs.AI · cs.CL

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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

we introduce PERCEIVE, a novel bilingual (English and Chinese) large-scale benchmark that, to the best of our knowledge, is the first to integrate five critical dimensions for social perception: author-created content, genuine readers' emotional feedback (derived from their comments), communication behavior, user attributes, and the social graph.

C2weakest assumption

That emotions annotated from reader comments accurately reflect genuine emotional responses and that the captured social graph and user attributes are sufficient to enable effective personalization across diverse readers.

C3one line summary

PERCEIVE is the first bilingual benchmark integrating author content, reader emotions from comments, communication behavior, user attributes, and social graphs for personalized social media emotion understanding.

References

94 extracted · 94 resolved · 2 Pith anchors

[1] From Generic Empathy to Personalized Emotional Support: A Self-Evolution Framework for User Preference Alignment 2025 · doi:10.18653/v1/2025.findings-emnlp.1024

[2] Exploring Persona Sentiment Sensitivity in Personalized Dialogue Generation 2025 · doi:10.18653/v1/2025.acl-long.900

[3] Proceedings of the AAAI conference on artificial intelligence , volume=

[4] DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning , author=. 2025 , pages= 2025

[5] Qwen2.5: A Party of Foundation Models , url =

Receipt and verification

First computed	2026-05-18T03:10:02.799604Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

1f7f7085d5fe342351c147c243c6289db06eeae86b969e9b03c735c4a0d0efbd

Aliases

arxiv: 2605.12525 · arxiv_version: 2605.12525v1 · doi: 10.48550/arxiv.2605.12525 · pith_short_12: D57XBBOV7Y2C · pith_short_16: D57XBBOV7Y2CGUOB · pith_short_8: D57XBBOV

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/D57XBBOV7Y2CGUOBI7BEHRRITW \
  | 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: 1f7f7085d5fe342351c147c243c6289db06eeae86b969e9b03c735c4a0d0efbd

Canonical record JSON

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    "abstract_canon_sha256": "93a0cc1426bbbf42ebd50d0cf34ac4e991f37484b10396422b69047a7cef6661",
    "cross_cats_sorted": [
      "cs.AI",
      "cs.CL"
    ],
    "license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
    "primary_cat": "cs.SI",
    "submitted_at": "2026-04-10T09:35:56Z",
    "title_canon_sha256": "f39dcc1f1b1c33653e76663244aaab536b6f801797020be18500f6505c1f30f4"
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  "source": {
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    "kind": "arxiv",
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