Pith Number

pith:NYK5YFIE

pith:2026:NYK5YFIE6I2RRYEUBT6KUFQWYD

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Amplification to Synthesis: A Comparative Analysis of Cognitive Operations Before and After Generative AI

Dongwook Yoon, Liz Cho

Cognitive operations on X shifted from retweet amplification in 2016 to synthesis of unique original posts in 2024, patterns consistent with generative AI.

arxiv:2605.13785 v1 · 2026-05-13 · cs.CY · cs.AI

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\pithnumber{NYK5YFIE6I2RRYEUBT6KUFQWYD}

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4 Citations open

5 Replications open

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Claims

C1strongest claim

Taken together, these patterns point toward an operational logic organized around active content generation and narrative-specific targeting - characteristics consistent with generative AI involvement.

C2weakest assumption

That the measured differences between 2016 and 2024 are caused by generative AI rather than by changes in platform algorithms, user behavior, API access, or election-specific events unrelated to AI.

C3one line summary

Election tweet analysis shows 2024 content is mostly original with low lexical overlap and narrative-focused timing, unlike the high-repetition retweet patterns of 2016, suggesting a move to AI-assisted synthesis in cognitive operations.

References

6 extracted · 6 resolved · 2 Pith anchors

[1] Characterizing the 2016 Russian IRA Influence Campaign 2026 · doi:10.48550/arxiv.1812.01997

[2] https://doi.org/10.3390/computers14100410 Barman, D., Guo, Z., & Conlan, O. (2024). The Dark Side of Language Models: Exploring the Potential of LLMs in Multimedia Disinformation Generation and Dissem 2024 · doi:10.3390/computers14100410

[3] https://doi.org/10.1038/s41467-018-07761-2 Defence, N. (2021, September 10). Fall 2021 NATO Innovation Challenge . https://www.canada.ca/en/department-national-defence/campaigns/fall-2021-nato-inn ova 2021 · doi:10.1038/s41467-018-07761-2

[4] Golovchenko, Y., Buntain, C., Eady, G., Brown, M. A., & Tucker, J. A. (2020). Cross-Platform State Propaganda: Russian Trolls on Twitter and YouTube during the 2016 U.S. Presidential Election. The Int 2020 · doi:10.1177/1940161220912682

[5] Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks 2024 · doi:10.1038/s41598-024-53755-0

Receipt and verification

First computed	2026-05-18T02:44:15.695737Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

6e15dc1504f23518e0940cfcaa1616c0d4830372b1a24509a55fa40cec3be384

Aliases

arxiv: 2605.13785 · arxiv_version: 2605.13785v1 · doi: 10.48550/arxiv.2605.13785 · pith_short_12: NYK5YFIE6I2R · pith_short_16: NYK5YFIE6I2RRYEU · pith_short_8: NYK5YFIE

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/NYK5YFIE6I2RRYEUBT6KUFQWYD \
  | 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: 6e15dc1504f23518e0940cfcaa1616c0d4830372b1a24509a55fa40cec3be384

Canonical record JSON

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      "cs.AI"
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    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CY",
    "submitted_at": "2026-05-13T17:06:52Z",
    "title_canon_sha256": "594099420def0194c5b1cb1b309a1a8a7de1b6e2278c9f961f02371ae169ed92"
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