Reddit Sentiment Report

Turn a buyer question into a cited report from public Reddit posts and comments.

What can Reddit Sentiment Report do?

Name a topic and the buyer point of view. The Actor searches public Reddit feeds, collects posts and comments, checks each quoted passage against its source, and saves a report plus the source rows.

What you get	Features
🧭 A buyer focused verdict with pros, cons, and themes	💬 Public Reddit post and comment collection
🔗 Source links and quotes checked against source text	📄 Markdown and JSON report files

Who this is for

• Check how buyers talk about a product
• Find repeated praise and complaints
• Collect source material for product research

What you get back

Field	Type	What you get	Example
id	string	Stable source identifier used in the dataset.	1vojjzh
topic	string	Topic requested for the report.	Framework Laptop
title	string	Title reported for the source item.	I really want a framework laptop, and finally got the money for one? What model should I get?
text	string	Complete transcript text for the media item.	I really want a framework laptop, and finally got the money for one? What model should I get? also any pro tips for parts or maintenance? *EDIT* guys I am us...
subreddit	string	Reddit community that supplied the item.	framework
url	string	Public video page analyzed by the Actor.	https://www.reddit.com/r/framework/comments/1vojjzh/i_really_want_a_framework_laptop_and_finally_got/
score	integer	Reddit score recorded when fetched.	0
comment_count	integer	Number of comments recorded when fetched.	0
kind	string	Whether the source is a post or comment.	post
created_at	string	Timestamp when the source item was created.	2026-08-14T21:06:26+00:00

The run also links to its dataset and any files named in the Actor output.

What you need to provide

Field	Type	Required	What it does	Example
topic	string	Yes	What should be researched on Reddit?	Framework Laptop
subreddits	array	No	Limit research to communities such as r/laptops (one search per subreddit). Leave blank to search all of Reddit.	``
buyerPerspective	string	No	Who is making the decision and what do they care about?	a prospective buyer evaluating whether this is right for them
maxPosts	integer	No	Upper bound on posts plus comments collected from Reddit's public feeds. Roughly 60% posts / 40% comments from the most relevant threads. 100 is enough for a solid report; 500 is the ceiling.	100
sort	string	No	Reddit search sort order applied to the post search.	relevance
timeRange	string	No	How far back the post search looks.	year
llm	object	No	Analysis model. Leave blank (or leave apiKey empty) to use the Actor's own inexpensive Bedrock model (nvidia.nemotron-nano-3-30b) , no key needed. To bring your own model, set all three: baseUrl of any /v1/chat/completions server, model, and apiKey (stored encrypted). Without an apiKey, baseUrl/model are ignored.	{"model":"nvidia.nemotron-nano-3-30b","baseUrl":"https://bedrock-runtime.us-east-1.amaz...

Quick start

1. Open the Actor in Apify Console.
2. Click Try for free or Create a task.
3. Replace the sample values with your own input.
4. Click Start.
5. Open the dataset and the named output files when the run ends.

Pricing

• sentiment-report: $0.04 per sentiment report created.
• Failed or skipped work is not charged unless an event is listed in the run charges.
• Normal Apify compute and proxy costs may also apply.

Limits and honest notes

• Public Atom feeds do not provide reliable vote scores, so score may be 0.
• The report reflects the posts and comments collected for this run. It is not a survey of all Reddit users.
• If analysis fails, the Actor keeps the collected evidence and labels the result evidence_only.

Code and API

The examples below use the same values as the Apify Console sample.

Input JSON

{
  "topic": "Framework Laptop",
  "buyerPerspective": "a prospective buyer evaluating whether this is right for them",
  "maxPosts": 100,
  "sort": "relevance",
  "timeRange": "year",
  "llm": {
    "model": "nvidia.nemotron-nano-3-30b",
    "baseUrl": "https://bedrock-runtime.us-east-1.amazonaws.com/openai/v1",
    "apiKey": ""
  }
}

Real output sample

This excerpt comes from the real run named in the current marketplace release report.

{
  "id": "1ufgf7e",
  "title": "Is the Framework Laptop worth it?",
  "text": "Is the Framework Laptop worth it?\n\nI am going into college as a biochem major, and I want laptop. I have asked chatgpt what it recommends, and it has been absolutely glazing the Framework Laptop 13. What do you guys think? Also, I don't want any people working for Framework here, unbiased consumer opinions only.",
  "subreddit": "computers",
  "kind": "post",
  "url": "https://www.reddit.com/r/computers/comments/1ufgf7e/is_the_framework_laptop_worth_it/",
  "score": 0,
  "comment_count": 4,
  "created_at": "2026-06-25T17:21:27+00:00",
  "topic": "Framework Laptop"
}

curl

curl -X POST "https://api.apify.com/v2/acts/physealabs~reddit-sentiment-report/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d @input.json

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("physealabs/reddit-sentiment-report").call(run_input={'topic': 'Framework Laptop', 'buyerPerspective': 'a prospective buyer evaluating whether this is right for them', 'maxPosts': 100, 'sort': 'relevance', 'timeRange': 'year', 'llm': {'model': 'nvidia.nemotron-nano-3-30b', 'baseUrl': 'https://bedrock-runtime.us-east-1.amazonaws.com/openai/v1', 'apiKey': ''}})
items = client.dataset(run["defaultDatasetId"]).list_items().items

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('physealabs/reddit-sentiment-report').call({"topic": "Framework Laptop", "buyerPerspective": "a prospective buyer evaluating whether this is right for them", "maxPosts": 100, "sort": "relevance", "timeRange": "year", "llm": {"model": "nvidia.nemotron-nano-3-30b", "baseUrl": "https://bedrock-runtime.us-east-1.amazonaws.com/openai/v1", "apiKey": ""}});
const { items } = await client.dataset(run.defaultDatasetId).listItems();

You can call this Actor from an agent or LLM tool that can send HTTP requests to the Apify API. Keep the Apify token in a secret store.

FAQ

Does it need a Reddit API key?

No. It reads public Reddit feeds.

Can I limit the communities?

Yes. Add subreddit names to subreddits.

Can I bring my own LLM?

Yes. Set all values in llm, including the API key.