👽 Reddit Scraper - Posts, Comments & Subreddits

Reddit Sentiment Scraper - Posts, Comments & Sentiment Data

Reddit sentiment scraper: extract posts, comments and community insights from any subreddit

Turn Reddit into a structured dataset. This scraper collects posts and comments from subreddits, search results, and individual threads -- delivering titles, authors, upvote scores, comment text, timestamps, and flair data in a clean, export-ready format.

Reddit is one of the richest sources of authentic consumer opinion on the internet. Whether you are running market research, building a sentiment analysis pipeline, scouting content ideas, or monitoring brand mentions, this actor gives you programmatic access to the conversations that matter -- without API key management. Runs through Apify residential proxies, which Reddit requires.

Search availability (November 2026). Reddit has been asking for sign-in on its public search feed, and this Actor does not sign in. While that lasts, a search query returns nothing, and the run says so in its log and status message. Subreddit listings and post URLs are not affected.

To follow a brand or topic meanwhile, use the keyword filter: list the subreddits where it is discussed, add your words to keywords, and the run saves (and charges) only the posts that mention them.

What data can you extract?

Field availability, stated up front. score, upvoteRatio and commentCount are populated for subreddit posts and are null for search results. Comments carry their own score, plus depth and parentId, so a thread can be rebuilt as a tree. null means "Reddit did not publish it", not "zero". Post body is filled for self/text posts; link posts have no body by definition. This Actor requires Apify residential proxies: Reddit refuses datacenter IPs on every public endpoint.

Post data

Field	Type	Description
dataType	string	Record type identifier (post)
redditId	string	Reddit fullname, e.g. t3_1vrszc5
postTitle	string	Title of the Reddit post
author	string	Username of the post author
subreddit	string	Subreddit where the post was published
score	integer | null	Net upvote score. null for search results (Reddit's search feed omits it)
upvoteRatio	number | null	Share of votes that are upvotes, 0-1. null for search results
commentCount	integer | null	Total comments on the post. null for search results
body	string	Self-text of the post. Empty for link posts, which have none
url	string	Link URL (external link posts) or post permalink
postUrl	string	Direct Reddit permalink to the post
createdUtc	string	UTC timestamp of when the post was created
flair	string	Post flair or tag
postType	string	text, link, image, video, ...
domain	string	Domain of the linked article, for link posts
isStickied	boolean	Whether the post is pinned by moderators
scrapedAt	string	ISO 8601 timestamp of when the data was collected

Comment data

Field	Type	Description
dataType	string	Record type identifier (comment)
redditId	string	Reddit fullname, e.g. t1_p4fu45x
author	string	Username of the comment author
body	string	Full text of the comment
score	integer | null	Net upvote score of the comment. null when Reddit hides it, on a deleted comment, or when the thread page could not be read and the run fell back to the comment feed (the log says so)
depth	integer	Nesting level (0 = top-level comment, 1 = reply to it, etc.)
parentId	string	redditId of the comment this one replies to. Empty for top-level comments
url	string	Link to the comment itself
subreddit	string	Subreddit of the thread
createdUtc	string	UTC timestamp of when the comment was posted
postTitle	string	Title of the parent post
postUrl	string	Permalink to the parent post
scrapedAt	string	ISO 8601 timestamp of when the data was collected

Comments come in the order Reddit shows the thread sorted by top: each top-level comment followed by the replies shown under it. Up to 500 per post. Reply chains that Reddit folds behind "more replies" are not opened, and a link to a single comment returns that conversation from the comment feed, without votes.

Use cases

• Market research -- Understand what real users say about your product, your competitors, or your industry by mining relevant subreddits and search queries.
• Sentiment analysis -- Feed Reddit post and comment data into NLP pipelines to measure community sentiment around brands, product launches, or events.
• Content ideation -- Discover what questions people ask, what problems they face, and what topics generate the most engagement in your niche.
• Competitive intelligence -- Monitor competitor mentions across Reddit to track public perception and identify strengths or weaknesses in their offering.
• Academic research -- Collect structured datasets of online discussions for social science, linguistics, or communication studies.

Scraping a subreddit without the Reddit API

No API key, no app registration, no OAuth flow and no rate quota to budget around. You pass subreddit names and the Actor reads what a browser sees.

That matters beyond the setup time. Reddit's API applies per-app rate limits and requires an approved application, which is a real obstacle for a one-off market study or a client project you will run twice. Here the only limits are the ones you set: maxPostsPerSubreddit, and sortBy / timeFilter to choose the window.

sortBy: "top" with timeFilter: "year" gives you the community's greatest hits — the reference threads people link back to. sortBy: "new" gives you what is happening right now. Different questions, one run each.

Exporting posts and comments to CSV

Every row is flat, so the dataset opens straight in Excel, Sheets or a pandas dataframe with no unnesting.

includeComments: false returns one row per post — the shape you want for a spreadsheet. Turn it on and each comment becomes its own row alongside the posts, with dataType telling you which is which and depth showing how deep in the thread a comment sits. Filter on dataType after export and one run gives you both tables.

Fields that fill on essentially every post: postTitle, subreddit, author, body, url, commentCount and createdUtc. score and upvoteRatio come back for the large majority; Reddit hides them on a small share of threads, and the Actor leaves them null rather than guessing.

Finding customer pain points for market research

The research move is not reading a subreddit — it is sorting it. Two columns do most of the work.

commentCount finds the arguments. A post with a modest score and a high commentCount is a topic people disagree about, and disagreement is where the unmet needs are. A high score with few comments is usually applause: pleasant, not informative.

upvoteRatio finds the tension. A ratio near 1.0 is consensus. A ratio around 0.6 means the community is split, which is exactly where a product opportunity or a positioning risk lives.

Sort by commentCount descending, read the top twenty body fields, and you have the vocabulary your customers actually use — which is worth more to a landing page than any keyword tool.

Monitoring a subreddit for product feedback

Pass the subreddits where your customers talk, sort by new, and schedule the run. When Reddit's search feed is answering (see the search availability note above), searchQueries with your brand, your competitors, or the problem you solve widens that to all of Reddit.

Because createdUtc and redditId come back on every row, deduplicating against your last run is a one-line join: anything with an id you have not seen is new. That turns a scheduled run into a feedback stream rather than a repeated dump.

For a monitoring setup, sortBy: "new" with a short timeFilter keeps runs small and cheap. Watch commentCount on rows that mention you — a mention gathering replies needs a human answer today, not in next week's report.

Input parameters

Parameter	Type	Required	Default	Description
subreddits	array	No	[]	Subreddit names, e.g., "technology", "programming". r/technology and a full subreddit link work too
keywords	array	No	[]	Keep only subreddit posts whose title or text mentions one of these words or phrases. Only matching posts (and their comments, when comments are on) are saved and charged; each post carries matchedKeywords
searchQueries	array	No	[]	Keywords to search across all of Reddit. See the search availability note above
postUrls	array	No	[]	Links to Reddit posts to scrape comments from. Tracking parameters and links to a single comment are accepted
maxPostsPerSubreddit	integer	No	100	Maximum posts to read per subreddit (1--500). With keywords, this is how many posts are checked
includeComments	boolean	No	false	Whether to extract comments from each post
maxCommentsPerPost	integer	No	100	Maximum comments to extract per post (1--500)
includeVoteData	boolean	No	true	Fetch score, upvote ratio and comment count for subreddit posts. Costs extra residential bandwidth; turn off for cheaper, faster runs when you only need titles, authors, dates and text
sortBy	string	No	"hot"	How to sort posts: hot, new, top, or rising
timeFilter	string	No	"week"	Time period when sorting by top: hour, day, week, month, year, all
maxConcurrency	integer	No	3	Number of browser pages to run in parallel (1--10)

At least one subreddit, search query, or post URL must be provided.

Example output

{
    "dataType": "post",
    "postTitle": "What's the best programming language to learn in 2026?",
    "author": "dev_user123",
    "subreddit": "programming",
    "score": 1547,
    "commentCount": 342,
    "body": "I've been thinking about switching careers into software development. I have some experience with Python from college, but I'm wondering what the job market actually wants right now. Any advice?",
    "url": "https://old.reddit.com/r/programming/comments/abc123/whats_the_best_programming_language/",
    "postUrl": "https://old.reddit.com/r/programming/comments/abc123/whats_the_best_programming_language/",
    "createdUtc": "2026-02-28T15:30:00Z",
    "flair": "Discussion",
    "isStickied": false,
    "scrapedAt": "2026-03-01T12:00:00.000Z"
}

{
    "dataType": "comment",
    "author": "senior_eng_42",
    "body": "Honestly, it depends on what you want to do. For web development, JavaScript/TypeScript is still king. For data science and ML, Python is non-negotiable. For enterprise backend work, Java and Go are in very high demand.",
    "score": 892,
    "depth": 0,
    "parentId": "",
    "url": "https://www.reddit.com/r/programming/comments/abc123/comment/def456/",
    "createdUtc": "2026-02-28T16:15:00Z",
    "postTitle": "What's the best programming language to learn in 2026?",
    "postUrl": "https://old.reddit.com/r/programming/comments/abc123/whats_the_best_programming_language/",
    "scrapedAt": "2026-03-01T12:00:00.000Z"
}

How much does it cost?

This actor uses a pay-per-event pricing model. You are charged a small start fee per run plus a fee for each data record (post or comment) that is successfully extracted. Current rates are shown on the Pricing tab of the Actor page.

There are no monthly subscriptions or minimum commitments. You only pay for the data you extract.

Tips and tricks

• Use search queries for broad research. Subreddit scraping is best for focused communities. To look for a brand or topic across all of Reddit there is the searchQueries input, which depends on Reddit's public search feed (see the search availability note above).
• Enable comments selectively. Comments multiply the number of results quickly. If you only need post-level data (titles, scores, dates), leave includeComments set to false to keep costs low and runs fast.
• Sort by "top" for high-signal data. When researching popular opinions or frequently recommended products, sort by top with a time filter of month or year to surface the most upvoted content.
• NSFW subreddits are supported. The scraper handles Reddit's age verification prompts automatically, so you can scrape any publicly accessible subreddit.

FAQ

How do I scrape Reddit posts and comments from a subreddit? Enter one or more subreddit names, choose a sort order (hot, new, top, or rising), set how many posts you want, and optionally enable comments. The scraper returns titles, authors, upvote scores, body text, timestamps, and flair as a clean dataset you can export to JSON, CSV, or Excel.

Do I need an API key or Reddit account to use this Reddit scraper? No. There is no Reddit API key, OAuth app, or login to manage. You just provide subreddits, search queries, or post URLs and the actor returns the public data directly.

Why use this instead of the official Reddit API? The official Reddit API now has strict rate limits, paid access tiers, and approval requirements that make large-scale or commercial scraping painful. This actor needs no API credentials, has no per-app rate-limit ceiling to manage, and lets you scrape posts plus their comment threads across many subreddits in one run.

What is a good Reddit API alternative for sentiment analysis? This actor is a practical Reddit API alternative for sentiment and market research: it pulls posts and comment text (with upvote scores and depth) ready to feed straight into NLP or LLM pipelines, without the cost and quota headaches of the official API.

Can I use this for sentiment analysis and brand monitoring? Yes. Scrape the subreddits where the brand, product, or topic is discussed (and add searchQueries when Reddit's search feed is answering, see the note above), enable comments, and feed the post and comment text into your sentiment model. Sort by top with a month or year time filter to surface the highest-signal opinions.

Is scraping public Reddit data legal? This tool collects only publicly accessible posts and comments. You are responsible for complying with Reddit's terms, applicable laws such as GDPR and CCPA, and using the data ethically. Avoid collecting personal data without a lawful basis.

Automate it

Add this Reddit scraper to an Apify Schedule to monitor a subreddit or a set of threads automatically every day or week — ideal for ongoing sentiment tracking and competitive intelligence. Connect the output to Make, n8n, Zapier, Google Sheets, Slack, or a webhook through Apify integrations so new posts and comments flow straight into your dashboards, alerts, or NLP pipeline. Recurring runs keep your sentiment dataset continuously fresh.

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