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November 2025 Issue!

Happy Thanksgiving from Team SimPPL!

This Thanksgiving, we're grateful for the community that's made our work possible. Over the past three years, students, researchers, and partners from around the world have joined us in building tools for a more transparent internet. Today, we're excited to share what we've been working toward together.

We're announcing the public beta launch of Arbiter, a social sensemaking platform that helps users trace and understand discourse across the social web.

Introducing Arbiter

Arbiter

What is Arbiter?

Making sense of the endless number of narratives across communities like X, Instagram, Reddit, and any social media platform is challenging. Narratives fragment as they spread online. A story about the 24-hour news cycle can start on one platform and take on a whole new meaning on another.

So, how do you trace a narrative when it splinters into dozens of variations across platforms?

Approach to Social Sensemaking

Arbiter is an AI-powered platform that analyzes discourse across multiple social media platforms.

Features

  • Trace narrative evolution across YouTube, Reddit, Bluesky, Instagram, X, and other social platforms to see how public conversations shift over time.
  • Analyze key entities including actors, organizations, regions, and products, and understand how they appear in discussions, including frequency, reach, stance, and thematic context.
  • Identify micro-influencers who shape conversations within specific subcommunities.
  • Surface emerging concepts using large language models to group and structure issue-specific conversations.
  • Map community structures with our social sensemaking AI agents that identify clusters, relationships, and discussion pathways across online spaces.

How Early Partners Use Arbiter

  • Protect Wikipedia's integrity: Editors understand how their articles are shared across social platforms, providing context that prevents misinterpretation and manipulation.
  • Combat financial fraud: Map networks of microinfluencers pushing predatory gambling and crypto investment schemes to vulnerable users.
  • Expose influence operations: Enable journalists to trace AI-slop-based information campaigns influencing public opinion.
  • Advance AI safety: Conducted product safety research for OpenAI models by identifying communities and actors sharing ChatGPT and Nanobanana "jailbreaking recipes" on Reddit and Telegram to understand emerging risks.

Explore Arbiter: arbiter.simppl.org

Contact us: team@simppl.org

What we are reading at SimPPL

Technical

4chan Data Breach

A major breach hit 4chan, with the attacker claiming to have dumped the platform's entire database. If true, this could expose years of user posts, IP logs, and moderation records, making it one of the largest leaks of an online forum.

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Perplexity for the Dark Web

A security researcher has built a Perplexity-style search engine for the dark web, enabling structured discovery of hidden marketplaces and forums. It showcases how LLM-style retrieval can be adapted to monitor threat intelligence in unindexed environments.

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AI in Google Sheets

Google has integrated AI directly into Sheets, allowing users to generate complex formulas automatically. This turns spreadsheets into more intelligent, assisted environments, reducing manual formula writing and improving data workflows.

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Research

Instacart's LLM-Powered Search

Instacart detailed how it integrated LLMs to improve e-commerce search, focusing on query understanding, disambiguation, and better matching of user intent to products. The system leverages hybrid retrieval and semantic ranking to bridge the gap between natural language queries and structured product catalogs.

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Misinformation and Adolescents

A recent Nature study explores how misinformation impacts adolescents, examining emotional vulnerability, cognitive development, and social influence. It highlights why young people are particularly susceptible to misleading content and outlines interventions to improve resilience and digital literacy.

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Text-to-SQL Benchmarks

A curated overview of resources for building and evaluating text-to-SQL systems, including benchmark datasets, model architectures, and workflow guides. These materials support developers studying schema linking, SQL generation reliability, and robust evaluation of natural language interfaces to databases.

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Policy

YouTube Ending Fact-Checking

YouTube reportedly signaled it may end fact-checking efforts, raising concerns about misinformation risks on the platform. The referenced document appears to be from January 2025, so it may not reflect November developments.

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Public Attitudes to AI Study

A recent survey examined public views on AI in the UK and US, highlighting perceptions of trust, risk, and expectations around regulation. It provides an overview of how citizens interpret rapid AI developments and their societal impact.

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International AI Safety Report

An international AI safety report chaired by Yoshua Bengio brought together experts and representatives from 30 countries, OECD, EU, and the UN. It outlines risks from advanced AI systems and proposes global governance mechanisms to address them.

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Data

Model Context Protocol (MCP)

Anthropic's Model Context Protocol introduces a unified standard for connecting LLMs with applications, tools, and data sources. It represents a major shift in AI agent architecture by enabling consistent, modular, and interoperable interactions, making it a foundational protocol for future AI system design.

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Refine.ink Research Review Tool

Refine.ink is an AI-powered platform designed for academic workflows, offering paper proofreading, consistency checking, and automated error detection. Highly praised by leading researchers, it streamlines research writing and validation, making it a valuable tool for scholars working with dense methodological work.

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FastAPI–MCP Integration

A lightweight integration layer allowing any FastAPI application to be converted into an MCP-compatible server with minimal setup. This enables rapid creation of AI-accessible tools, making it easier to connect existing APIs with agentic workflows and LLM-based systems.

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