How to track Jane Doe trial chatter on Reddit: guide

Overview

If you’re trying to follow how Reddit talks about the Diddy trial and the anonymous "Jane Doe" accuser, you quickly hit a wall: thousands of comments, fast–moving threads, and plenty of speculation. For a business owner, agency, or marketer, the real value isn’t in the drama, but in understanding public conversation, sentiment, and misinformation risk. Below are three practical tiers: manual research, no‑code automation, and fully agentic workflows with an AI computer agent like Simular.

1. Manual / Traditional Ways (3–10 methods)

1) Basic Reddit search and filters

• Go to Reddit and use the search bar for queries like "Diddy trial", "Jane Doe" Diddy, or case–related docket numbers.
• Use filters: sort by "Top" for historically big threads, "New" for breaking discussion, and set time range (Past 24 hours, Week, Month).
• Open promising posts in new tabs and skim for context: what people think happened, what sources they cite, and what subreddits host the most reasoned talk.
• Log key links and themes in a spreadsheet (columns: URL, subreddit, date, summary, sentiment, notes).

2) Subreddit–by–subreddit monitoring

• Identify relevant communities (e.g., r/news, r/hiphopheads, r/popculturechat, or legal‑oriented subs that allow case discussion).
• For each subreddit, click the search field and repeat targeted queries.
• Sort by "New" to catch fresh posts; manually check once or twice a day.
• Note recurring talking points, reputable sources (mainstream news, legal filings), and recurring misinformation.

3) Use Reddit Saved Posts as a simple queue

• When you find a valuable thread, click "Save" beneath the post.
• Access all saved posts from your user profile; this becomes your manual research queue.
• Once you’ve processed a thread into your notes or dashboard, unsave it to keep the queue tidy.

4) Build a simple trial log in Google Sheets

• Create columns: Date, Subreddit, Post Title, Link, Mentions of Jane Doe (Y/N), Core Claim, Evidence Cited, Sentiment (–/0/+), Action for Brand.
• After each research session, batch–enter posts you found.
• Color–code rows by sentiment or risk level so patterns are visible at a glance.

5) Manually check Reddit policies to stay compliant

• Before engaging, read the Reddit Content Policy and Reddit Help Center.
• Avoid doxxing, speculation about Jane Doe’s identity, or brigading; keep your work to analysis of public conversation, not individuals.

These manual methods are precise but time–consuming. Once you understand your ideal queries, move to light automation.

2. No‑Code Automation Methods

1) RSS or email alerts with third‑party tools

• Some third‑party services let you create RSS feeds or email alerts for specific Reddit searches or subreddits.
• Configure a feed that tracks posts containing "Diddy" and "Jane Doe" in chosen subreddits.
• Pipe the feed into tools like Notion, Google Sheets (via Google Apps Script), or an RSS dashboard.
• Pros: low setup, passive monitoring. Cons: limited control over filtering and no deep analysis.

2) Zapier / Make to log Reddit links automatically

• Use a Reddit–integrated zap/automation (if available) or a third‑party Reddit trigger.
• Trigger: "New post matching search" or "New post in subreddit".
• Action: create a new row in Google Sheets or Airtable with fields: title, URL, subreddit, author, created_at.
• Layer a second step that tags the row if the title or body contains key phrases (e.g., Jane Doe, trial date, court filing).
• Pros: no code, central log built for you. Cons: content still needs human review and summarization.

3) Use a no‑code text‑analysis API

• Connect your sheet to a text analysis service (sentiment, keyword extraction) via Make or Zapier.
• On each new row, send the post text to the API.
• Store back: sentiment score, main themes (e.g., "legal process", "conspiracy", "victim blaming").
• Pros: first level of structured insight. Cons: still fragmented across tools; no full workflow control.

At this stage you’ve reduced some busywork, but you’re still the glue. To really scale, you want an AI computer agent that can operate your actual desktop and browser like a research analyst.

3. At‑Scale Automation with an AI Agent (Simular)

Sai is built to do what a human researcher would do across the entire desktop and browser – only faster and without getting tired.

Method 1: Autonomous Reddit research and logging

• Define a clear task for your Simular agent: "Every morning, open Reddit, search for Diddy trial and Jane Doe, scan top 30 posts across r/news, r/hiphopheads, r/popculturechat, summarize key themes into a Google Sheet, and highlight any new reputable sources or court updates."
• In Sai, you let the agent control your browser: navigate to Reddit, run searches, open posts, scroll comments.
• It copies relevant text, categorizes it (topic, sentiment, risk), and writes structured rows into Sheets or Docs.
• Pros: fully hands‑off daily research; transparent execution logs show every step and click. Cons: requires initial setup and some monitoring early on.

Method 2: Cross‑channel context building for campaigns

• Extend the workflow: after logging Reddit insights, have the agent open your CRM or campaign doc.
• It can summarize "What Reddit is saying about the Diddy trial and Jane Doe this week" into a short brief for your sales or comms team.
• The agent can generate talking‑point lists, risk flags (e.g., "avoid referencing unverified allegations"), and suggested disclaimers.
• Pros: transforms raw chatter into usable strategy; ideal for agencies with multiple clients. Cons: you must set guardrails so the agent never engages, only observes and summarizes.

Method 3: Long‑horizon monitoring with production‑grade reliability

• Simular is designed for workflows with thousands or millions of steps. You can schedule ongoing monitoring:
  • Weekly deep dives into major threads.
  • Monthly trend reports on how Reddit sentiment around the trial shifts.
• Because Simular’s execution is transparent, you can inspect each action if a client questions your findings.
• Pros: scalable, auditable research pipeline. Cons: you still need a human to decide what not to act on and how to respect legal/ethical limits.

For all AI‑powered approaches, always keep a human in the loop to ensure compliance with Reddit’s policies, avoid speculation about real‑world identities, and use the data strictly for analysis rather than targeted harassment or manipulation.