IO Factory: Simulating AI-Enabled Influence Campaigns at Scale [pdf]
![IO Factory: Simulating AI-Enabled Influence Campaigns at Scale [pdf]](/img-proxy?url=https%3A%2F%2Farxiv.org%2Fstatic%2Fbrowse%2F0.3.4%2Fimages%2Farxiv-logo-fb.png&w=1024){kind=logo}
Computer Science > Artificial Intelligence arXiv:2608.10920 (cs) [Submitted on 11 Aug 2026] Title:IO Factory: Simulating AI-Enabled Influence Campaigns at Scale Authors:Lukasz Olejnik, Wenchao Dong, Jonas R. The threat of digital manipulation now extends beyond persuasive text from individual language models to AI swarms, i.e., persistent groups of coordinated agents that adapt to platform feedback and disguise organized campaigns as ordinary social interaction. Because such campaigns cannot be identified from isolated messages alone, they must be analyzed across a continuous spectrum of planning, platform action, exposure, interpretation, measurement, and adaptation.
- ▪Computer Science > Artificial Intelligence arXiv:2608.10920 (cs) [Submitted on 11 Aug 2026] Title:IO Factory: Simulating AI-Enabled Influence Campaigns at Scale Authors:Lukasz Olejnik, Wenchao Dong, Jonas R.
- ▪The threat of digital manipulation now extends beyond persuasive text from individual language models to AI swarms, i.e., persistent groups of coordinated agents that adapt to platform feedback and disguise organized campaigns as ordinary s
- ▪Because such campaigns cannot be identified from isolated messages alone, they must be analyzed across a continuous spectrum of planning, platform action, exposure, interpretation, measurement, and adaptation.
Hacker News (AI / LLM) files mainly under ai. We currently carry 4,645 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
inspect →
Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | arXiv.org |
| Canonical URL | https://arxiv.org/abs/2608.10920 |
| Publication time | Wed, 12 Aug 2026 16:04:35 +0000 |
| Retrieval time | 2026-08-12T16:11:31.861Z |
| Last seen | 2026-08-12T16:11:31.861Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | xkxqMCymuxgf · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Computer Science > Artificial Intelligence arXiv:2608.10920 (cs) [Submitted on 11 Aug 2026] Title:IO Factory: Simulating AI-Enabled Influence Campaigns at Scale Authors:Lukasz Olejnik, Wenchao Dong, Jonas R. Kunst, Signe Riemer-Sørensen, Tobias Herb, Meeyoung Cha, Daniel Thilo Schroeder View a PDF of the paper titled IO Factory: Simulating AI-Enabled Influence Campaigns at Scale, by Lukasz Olejnik and 6 other authors View PDF HTML (experimental) Abstract:We introduce IO Factory, an AI-driven framework for simulating information and influence campaigns as fully integrated, traceable processes.
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv.org.
Discussion
0 commentsMore from arXiv.org
