Crowd Watch - A Reddit Mod Tool

App listing

[link]https://developers.reddit.com/apps/crowd-watch [link]https://github.com/AnushkaRatnaparkhi/crowd-watch

Inspiration

As a regular Reddit user, I had mostly experienced Reddit from the perspective of searching for answers and participating in communities. During this hackathon, I started exploring Reddit from the moderator side for the first time and realized how difficult it can be to quickly interpret suspicious activity inside chaotic discussion threads.

Moderators often have to manually piece together timelines, repeated phrases, participation patterns, spam bursts, dogpiling behavior, and possible brigading signals across large threads. I wanted to build something that felt less like an automated moderation bot and more like a moderation investigation assistant that helps moderators understand what changed in a thread and why it may warrant review.

That idea became Crowd Watch.

What it does

Crowd Watch is a Reddit moderation investigation assistant built on Reddit’s Developer Platform. It analyzes Reddit threads and surfaces explainable behavioral signals such as:

• sudden engagement spikes
• repeated promotion patterns
• coordination-style phrasing
• topic drift
• suspicious reply-chain behavior
• concentrated participation patterns
• spam bursts and possible brigading signals

The app then converts these observations into structured moderation evidence that moderators can quickly review, copy, and use during investigations or escalation workflows.

Instead of automatically flagging users or making moderation decisions, Crowd Watch focuses on helping moderators interpret suspicious thread behavior faster and with more context.

How I built it

I built Crowd Watch using Reddit’s Developer Platform, Devvit, and TypeScript-based thread analysis logic. A large part of the development process involved prompt engineering and LLM-assisted coding to rapidly prototype moderation heuristics, signal classification flows, UI structures, and evidence formatting systems.

One major challenge was balancing useful AI-assisted moderation insights without making the system overly accusatory or misleading. Another challenge was working within Reddit Forms UI limitations while still keeping moderation evidence readable, structured, and easy to scan.

The system was intentionally designed around explainable behavioral signals rather than heavy UI dependency, which means future improvements, including stronger AI reasoning, richer interfaces, reply-network analysis, and additional moderation intelligence layers can extend the tool significantly over time.

What I learned

This project completely changed how I think about Reddit communities technically. Before this hackathon, I mostly understood Reddit as a user. Building Crowd Watch forced me to think much more deeply about moderation workflows, community health, behavioral ambiguity, and how trust should work inside moderation tooling.

I also learned that moderation tools become far more useful when they help moderators structure evidence and reduce cognitive load rather than trying to replace moderator judgment entirely.

Built With

• behavioral-signal-analysis
• devvit
• llm-assisted-coding
• node.js
• prompt-engineering
• reddit-developer-platform
• reddit-forms
• typescript