# Reddit Brand Mention Monitor (`coregent/reddit-brand-mention-monitor`) Actor Monitor Reddit for mentions of your brand, products, competitors and tracked keywords. New posts and comments with relevance, sentiment, complaint / praise / comparison / switching signals and only-new scheduled monitoring. No Reddit login or API key. - **URL**: https://apify.com/coregent/reddit-brand-mention-monitor.md - **Developed by:** [Delowar Munna](https://apify.com/coregent) (community) - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 brand mentions This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md. ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run. For examples already wired to this Actor's own input schema, see the [API](#api) section below. Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`). # README ## Reddit Brand Mention Monitor ![Reddit Brand Mention Monitor](https://raw.githubusercontent.com/coregentdevspace/reddit-brand-mention-monitor-assets/main/thumbnail-reddit-brand-mention-monitor.png "Reddit Brand Mention Monitor — Reddit posts and comments naming your brand, with relevance, sentiment and switching signals") **Track new Reddit posts and comments mentioning your brand, products and competitors — with relevance, sentiment and intent signals.** Give it your brand names, their aliases, your competitors and any keywords you care about. It searches Reddit (all of it, or the subreddits you choose), reads the posts **and the comments under them**, keeps only the ones that genuinely name what you track, and returns one clean row per mention: - which brand, alias, competitor or keyword matched, and **why** (a 0–100 relevance score with a point-by-point breakdown) - sentiment (POSITIVE / NEUTRAL / NEGATIVE / MIXED, −1…+1) - what kind of mention it is: complaint, praise, bug report, support issue, feature request, comparison, alternative request, switching, purchase intent, recommendation, question … - buying-intent and switching flags, and the competitors named alongside you - author, subreddit, text, link, publish time, Reddit score and comment count - for comments: the post they reply to Schedule it hourly or daily with **only-new mode** and you get each mention once, and pay for it once. No Reddit login, no API key, no cookies. No AI cost: classification is rule-based and explainable. *** ### What can I monitor? | Input | What it's for | Example | |---|---|---| | **Brands** | Your brands and products | `Notion`, `HubSpot`, `Canva` | | **Aliases** | Other spellings, attributed to the brand | `{ "OpenAI": ["Open AI", "ChatGPT", "chat gpt"] }` | | **Competitors** | Competitor brands — monitored too, and used to detect comparisons and switching | `Obsidian`, `Coda` | | **Keywords** | Campaigns, slogans, features, launches, founders | `Notion AI`, `#ShotOniPhone` | | **Subreddits** | Optional — restrict to these communities | `productivity`, `r/SaaS`, `https://www.reddit.com/r/Notion/` | Every term is matched **literally**, as a whole word or phrase, case-insensitive, in post titles, post bodies and comments. "CRM" matches "CRMs"; "Monday.com" and "C++" work as written. #### Can I use aliases? Yes. A match on `ChatGPT` comes back with `trackedTerm: "OpenAI"`, `canonicalBrand: "OpenAI"` and `matchedAlias: "ChatGPT"`. Aliases are never merged across brands unless you map them. An alias that contains its brand ("notion app" under "Notion") is not searched separately, because the brand search already finds it, but it is still matched and reported. #### Can I monitor competitors? Yes. Each competitor is searched and its mentions returned (`termType: "COMPETITOR"`). A post or comment that names your brand **and** a competitor is flagged `COMPARISON`, and phrases like "switched from X to Y", "alternative to X" or "X vs Y" set the switching, alternative and comparison signals. Turn **Search competitors** off to use competitors only for classifying mentions of your own brands; that halves the searches. #### Do you scan posts and comments? Both, by default. Every post that names a tracked term has its first comments read (top comments first, up to **Max comments per post**), and every comment that names a term is a mention row too. Complaints, recommendations and "we switched away from it last month" are very often in the replies. A comment must name a term itself. A reply in a Notion thread that never says "Notion" is not counted: in testing, that rule kept chatter like "why do so many people need a system?" out of the results. #### Can I monitor all of Reddit? Can I limit it to subreddits? Leave **Subreddits** empty to search all of Reddit, or list communities to search each of them. A subreddit named after your brand (r/Notion) raises relevance, and so does any subreddit you selected. *** ### Only-new monitoring #### What does only-new mode do? With **Only new mentions** on, the Actor remembers every mention it delivered under your **Monitor key**, in a named key-value store on your account (`reddit-brand-monitor-`). Later runs with the same key return, and charge for, only mentions it has not delivered before. Mentions it has seen are counted in the run summary as `alreadySeenMentions` and are free. An edited post keeps its ID, so an edit is never delivered twice. Use the same monitor key on every scheduled run. Without one, a key is derived from your terms and subreddits, so changing them starts a fresh memory. With a key set and only-new mode **off**, everything is delivered and rows still say whether they are new (`isNew`, `firstSeenAt`). #### What happens on the first monitoring run? You choose, with **First run**: - `RETURN_CURRENT` (default): the first run returns the current mentions in your time window, and remembers them. - `BASELINE_ONLY`: the first run remembers the current mentions **without returning or charging any**. From the second run on, you get only mentions that appeared after it. Use this when you want a clean feed of genuinely new mentions from day one. #### Can I schedule hourly or daily? Yes, that is what it is built for. Use **Posted within** = `HOUR` or `DAY`, **Search sort** = `NEW`, only-new mode on and a fixed monitor key, then add a schedule in Apify Console. Each run stops collecting shortly before its timeout and delivers what it has found, so a long run is never wasted. *** ### Relevance, sentiment and signals #### What does the relevance score mean? 0–100, built from named factors that are all listed in `relevanceBreakdown`: | Factor | Points | |---|---| | Brand, alias, competitor or keyword named | 40 | | Named in the post title | +20 | | Named in a comment whose post names a tracked term too | +10 | | Named more than once | +10 | | Product words nearby ("app", "pricing", "support", "switched", "bug" …) | +15 | | Brand and competitor named together | +10 | | Subreddit named after the term · or a subreddit you selected | +15 · +5 | | A Capitalised one-word brand seen only in lower case with nothing product-like nearby ("an apple") | −20 | | Bot, link dump or copy-paste promotion | −60 | | Free search result whose body could not be read (see Limitations) | 15 | **Minimum relevance** (default 30) drops everything below it. For ambiguous brand names (Apple, Monday, Linear, Square) raise it and add **Exclude words** ("apple pie", "linear algebra"). **Common-word brands are protected by case.** When a one-word brand like Linear or Apple appears only in another case ("linear algebra", "FORECAST.LINEAR"), the mention is dropped unless something backs it up: the subreddit is named after the brand, another tracked term is named alongside it, or it is a comment on a post that writes the brand as "Linear". Product words nearby ("using", "model") are not enough on their own. These drops are counted as `ambiguous-common-word` in the run summary. #### Is sentiment included? Yes: `sentiment` and `sentimentScore` (−1…+1). It is read where your brand is named, not across the whole text, so "Notion is great for docs. Obsidian is a mess." is positive for Notion. A post whose title names the brand is read whole, but the title counts double and body sentences that don't name the brand count half, so praise for the tool someone is moving to doesn't make leaving yours positive. The title also leads the category: "Ditching Notion due to database lag" is about leaving Notion, whatever the rest of the post covers. Negation ("not great", "wouldn't recommend") and intensifiers are handled, and in a question positive words are ignored ("Is Notion any good?" is neutral). It is inferred by rules and will sometimes be wrong; treat it as a signal. #### Are buying and switching signals included? Yes. `signals` can hold `BUYING_INTENT`, `SWITCHING_INTENT`, `ALTERNATIVE_REQUEST`, `COMPARISON_INTENT`, `SUPPORT_INTENT`, `RECOMMENDATION_INTENT`, `CANCEL_OR_CHURN_INTENT` and `FEATURE_REQUEST`, and `buyingIntent` / `switchingIntent` are booleans. Switching and buying count only when the **writer** is doing it ("we switched from Notion", "thinking of leaving Notion", "should I upgrade?"). "You should switch from Notion" is advice, not churn. A quoted example of what other people say is ignored. `primaryCategory` is the most specific category that fired, in this order: BUG_REPORT, SUPPORT_ISSUE, COMPLAINT, SWITCHING_INTENT, ALTERNATIVE_REQUEST, PURCHASE_INTENT, COMPARISON, FEATURE_REQUEST, RECOMMENDATION, PRAISE, PRODUCT_FEEDBACK, QUESTION, CAMPAIGN_MENTION, otherwise GENERAL_MENTION. The others are in `secondaryCategories`, and `matchedPhrases` shows the text that triggered them. Each of these outputs can be switched off (**Sentiment**, **Mention category**, **Intent signals**, **Buying-intent flag**); a switched-off field is `null`, so every row keeps the same columns. #### Is AI required? No. Every classification is rule-based, runs inside the Actor and costs nothing extra. Rules are predictable and explainable: you can always see the phrase behind a label. #### How are duplicate mentions handled? One row per post or comment. A post found by three searches, or naming both your brand and a competitor, is **one** row with every term in `matchedTerms`, `canonicalBrands`, `matchedAliases` and `matchedCompetitors`, and is charged once. `duplicatesMerged` in the run summary counts them. *** ### Input examples **One brand across Reddit, past week:** ```json { "brands": ["Notion"], "timeRange": "WEEK", "sort": "NEW", "scanComments": true } ``` **Brand with aliases, past 24 hours, stricter relevance:** ```json { "brands": ["OpenAI"], "aliases": { "OpenAI": ["Open AI", "ChatGPT", "chat gpt"] }, "timeRange": "DAY", "minimumRelevance": 40 } ``` **Competitor monitoring in chosen subreddits:** ```json { "brands": ["HubSpot"], "competitors": ["Salesforce", "Pipedrive"], "subreddits": ["sales", "SaaS"], "timeRange": "MONTH", "includeSentiment": true, "includeIntent": true } ``` **Daily only-new monitor (schedule this):** ```json { "brands": ["Notion"], "subreddits": ["productivity", "Notion"], "timeRange": "DAY", "sort": "NEW", "onlyNewMentions": true, "monitorKey": "notion-brand-monitor", "scanComments": true } ``` **Start a monitor with a baseline (first run returns nothing):** ```json { "brands": ["ExampleBrand"], "onlyNewMentions": true, "monitorKey": "example-brand", "baselineMode": "BASELINE_ONLY" } ``` > When you paste JSON into the Console, state every on/off option you care about. The Console can store an option you leave out as `false` even when its default is on. *** ### Output One row per mention. The dataset has three views, each a different cut of the same rows, and every row carries every field. The records below are real, from a run of the first input example (`Notion`, all of Reddit, past week) on 2026-10-16. Usernames are anonymised and long text is trimmed. #### Mentions: what was said, where, by whom ![Reddit Brand Mention Monitor — Mentions view, table (term, source, subreddit, post title, text, thread, relevance, sentiment, category, new)](https://raw.githubusercontent.com/coregentdevspace/reddit-brand-mention-monitor-assets/main/reddit-brand-mention-monitor-output-mentions-table-view.png "Reddit Brand Mention Monitor — Mentions view, table") One row from that table, as JSON: ```json { "trackedTerm": "Notion", "canonicalBrand": "Notion", "sourceType": "COMMENT", "subreddit": "Notion", "title": null, "text": "I've used Notion on different browsers on Windows, and there is lets me open multiple tabs for Notion. I typically right click on something and choose open in a new tab. Do you have that option in your browser?", "parentPostTitle": "Is there a working Notion client for Linux? Web version lacks page tabs", "author": { "username": "example_user_1", "profileUrl": "https://www.reddit.com/user/example_user_1/" }, "url": "https://www.reddit.com/r/Notion/comments/1x7fgni/is_there_a_working_notion_client_for_linux_web/ph40wk6/", "publishedAt": "2026-10-16T14:04:24.924Z", "score": 1, "commentsCount": null, "relevanceScore": 90, "sentiment": "NEUTRAL", "primaryCategory": "GENERAL_MENTION", "isNew": true, "firstSeenAt": "2026-10-16T18:10:03.071Z" } ``` `commentsCount` is for posts; a comment row carries its post's title, ID and link instead. #### Sentiment & signals: complaints, switching, buying intent ```json { "trackedTerm": "Notion", "sourceType": "POST", "subreddit": "ObsidianMD", "title": "Ditching Notion due to database lag and AI nagging, how are experiences with rollups, local flashcards, and GitHub sync (Linux/Windows)?", "text": "Notion’s database lag has finally pushed me to find a replacement. My workspace has become very heavy with large reference databases, review decks/flashcard setups, and relations/rollups, and the web app is crawling. … I’m looking at migrating to Obsidian to keep everything fast, local, and version-controlled …", "sentiment": "NEGATIVE", "sentimentScore": -0.69, "primaryCategory": "COMPLAINT", "secondaryCategories": ["SWITCHING_INTENT", "QUESTION"], "signals": ["SWITCHING_INTENT"], "buyingIntent": false, "switchingIntent": true, "matchedCompetitors": [], "matchedPhrases": ["ditching"], "url": "https://www.reddit.com/r/ObsidianMD/comments/1x7ebzu/ditching_notion_due_to_database_lag_and_ai/" } ``` The body praises the tool the writer is moving to ("fast, local"). It doesn't make leaving Notion positive, because body sentences that don't name your brand count for less than the title and the sentences that do. Had `Obsidian` been a competitor in the input, it would appear in `matchedCompetitors` and the row would also be a `COMPARISON`. #### Why it matched: the evidence behind every row A reply to that post, "Rollups on notion are a broken relational database system. That's why it lags…": ```json { "trackedTerm": "Notion", "termType": "BRAND", "canonicalBrand": "Notion", "matchedAlias": null, "matchedTerms": ["Notion"], "matchType": "DIRECT", "relevanceScore": 30, "relevanceSignals": ["EXACT_BRAND_MATCH", "PARENT_POST_MATCH"], "relevanceBreakdown": [ { "factor": "EXACT_BRAND_MATCH", "points": 40 }, { "factor": "PARENT_POST_MATCH", "points": 10 }, { "factor": "AMBIGUOUS_LOWERCASE", "points": -20 } ], "textAvailable": true, "searchQueries": ["Notion"], "sourceId": "t1_ph3g4kj", "parentPostUrl": "https://www.reddit.com/r/ObsidianMD/comments/1x7ebzu/ditching_notion_due_to_database_lag_and_ai/", "url": "https://www.reddit.com/r/ObsidianMD/comments/1x7ebzu/ditching_notion_due_to_database_lag_and_ai/ph3g4kj/", "scrapedAt": "2026-10-16T18:11:05.845Z" } ``` The comment writes "notion" in lower case, which could be the ordinary word, so it loses 20 points. It is kept because the post it replies to names Notion, which corroborates it and adds 10. On its own, the same sentence would be dropped as `ambiguous-common-word`. `relevanceBreakdown` always adds up to `relevanceScore` (`relevanceSignals` lists the positive factors). **Every row also has:** `rowType`, `matchedAliases`, `matchedKeywords`, `canonicalBrands`, `postId`, `commentId`, `parentPostId`, `monitorKey`, `capturedSequence`. A field that doesn't apply is `null` rather than missing, so CSV and Excel exports keep one shape. #### Run summary Each run writes two records to its key-value store: - **`RUN_SUMMARY`**: tracked terms, search operations, posts and comments scanned, qualifying / new / already-seen mentions, positive / negative / complaint / comparison / switching / buying-intent counts, duplicates merged, every drop reason, and **`observedMentionVelocity`**: mentions in the last hour, 24 hours and 7 days, plus per-term counts. Velocity counts what this run found, which is bounded by **Max posts per term** and **Posted within**. It is not total platform volume. - **`SOURCE_SUMMARY`**: the outcome of every search: `SUCCESS`, `NO_RESULTS`, `INVALID_TERM`, `INVALID_SUBREDDIT`, `SUBREDDIT_NOT_FOUND`, `RATE_LIMITED`, `BLOCKED`, `PARTIAL_RESULT`, `TEMPORARY_REDDIT_ERROR`. One failed term or subreddit never fails the run. *** ### How does pricing work? Pay per event: you are charged **once per unique qualifying mention delivered** to your dataset. You are never charged for searches, for posts and comments that were scanned but didn't qualify, for mentions below your minimum relevance or caught by your filters, for duplicates, for mentions your monitor has already delivered, for a `BASELINE_ONLY` first run, for retries, or for failed searches. A run that finds nothing costs you nothing in events. See the **Pricing** tab for the current rate. This README deliberately doesn't quote figures, because they can change. If you set a maximum charge per run, the Actor stops there and delivers the **most relevant** mentions first. *** ### Can I use it through the API or MCP? Yes, like any Apify Actor: run it with the [Apify API](https://docs.apify.com/api/v2), the JavaScript or Python client, or from AI agents through the [Apify MCP server](https://mcp.apify.com/). Read results from the run's default dataset, and `RUN_SUMMARY` from its key-value store. ```bash curl -X POST "https://api.apify.com/v2/acts/coregent~reddit-brand-mention-monitor/run-sync-get-dataset-items?token=" \ -H "Content-Type: application/json" \ -d '{ "brands": ["Notion"], "timeRange": "DAY", "onlyNewMentions": true, "monitorKey": "notion-daily" }' ``` *** ### Limitations - **Relevance is literal, not semantic.** A mention must contain the term. A post about your product that never names it is not found, and an unrelated use of a common word can slip through. That is what **Exclude words** and **Minimum relevance** are for. - **Search depth is bounded.** Reddit's search returns roughly 250 results per query, sort and time window. For busy brands use short windows (`DAY`, `HOUR`) on a schedule rather than one huge search. - **Comments are read from the top of each thread.** Logged-out Reddit serves a thread's first page of comments (plus a few expansions), so very long threads are sampled, not read in full. - **Occasionally a post's body can't be read.** If the search route that returns full post bodies is unavailable, posts come from Reddit's own search results, which carry the title only. Reddit's search also matches ordinary words in the hidden body ("a notion of…"), so such a post scores only 15, below the default minimum relevance. It qualifies only in a subreddit named after the term, and it has `matchType: "SEARCH_MATCH"` and `textAvailable: false`. Its comments are read only when you selected subreddits or it is in a subreddit named after the term. Each comment must still name the term itself. - **Sentiment and categories are inferred** by rules and can be wrong, especially for sarcasm. Every label shows the phrases behind it. ### 🚦 Proxy policy Use **Apify Datacenter** proxy (the default) or **no proxy**. Both work reliably for Reddit search and comment pages at this Actor's conservative pacing. **Apify Residential proxy is not supported.** The Actor fails at startup if `apifyProxyGroups` includes `RESIDENTIAL`. Reason: in pay-per-event Actors, residential bandwidth is billed to the developer, not the run user, and Reddit comment pages are large, so a single bandwidth-heavy run could cost more than it earns. If you genuinely need residential routing, supply your own residential provider in the proxy editor's **Custom proxy URLs** field. That traffic goes through your provider, not Apify, and is unaffected: ``` http://user:pass@proxy.iproyal.com:12321 http://user:pass@proxy.brightdata.com:22225 http://user:pass@proxy.oxylabs.io:7777 ``` ### Responsible use - This is an unofficial tool, not affiliated with or endorsed by Reddit. - It reads **public** posts and comments only. No login, no private data, no email discovery. - Sentiment and intent are inferred and may be imperfect. Do not make decisions about individuals from them. - Follow each subreddit's rules if you respond to a mention. Never use the output for spam, harassment, vote manipulation or automated replies; this Actor does none of those, and you shouldn't build them on top of it. - You are responsible for processing the data lawfully (GDPR / CCPA and similar) in whatever you do downstream. ### Related Coregent Actors - **[Reddit Leads / Purchase Intent Finder](https://apify.com/coregent/reddit-leads-purchase-intent-finder)**: turn high-intent mentions into scored leads, one row per person. - **[Reddit Posts Search Scraper](https://apify.com/coregent/reddit-posts-search-scraper)**: full Reddit search results, every field. - **[Reddit Comments Scraper](https://apify.com/coregent/reddit-comments-scraper)**: complete comment trees for any thread. - **[Reddit User Scraper](https://apify.com/coregent/reddit-user-scraper)**: profile details for the authors you find. # Actor input Schema ## `brands` (type: `array`): Your brands and products, one per line, e.g. Notion, HubSpot, Canva. Each is searched on Reddit (all of Reddit, or each subreddit below) and every post and comment that names it becomes a mention row. Required unless you give keywords; with neither, the run monitors the example brand Notion. ## `aliases` (type: `object`): Other spellings of each brand, as JSON: { "OpenAI": \["Open AI", "ChatGPT"] }. A match on an alias is attributed to its brand (canonicalBrand) and named in matchedAlias. An alias is only searched separately when it does not already contain the brand name; "notion app" is found by the Notion search. ## `competitors` (type: `array`): Competitor brands, e.g. Obsidian, Coda. Their mentions are monitored too, and a mention that names your brand and a competitor is flagged as a comparison. Phrases like "switched from X to Y" or "alternative to X" set the switching and alternative signals. ## `keywords` (type: `array`): Other tracked terms: campaign names, slogans, product features, launches, founders. Matched and searched like brands, with no canonical brand attached. ## `subreddits` (type: `array`): Restrict the search to these communities. SaaS, r/SaaS and https://www.reddit.com/r/SaaS/ all work. Leave empty to search all of Reddit. ## `searchCompetitors` (type: `boolean`): Run a separate Reddit search for each competitor. Turn off to use competitors only to classify mentions of your own brands (comparisons, switching); this halves the searches when you list as many competitors as brands. ## `scanPosts` (type: `boolean`): Return posts whose title or body names a tracked term. ## `scanComments` (type: `boolean`): Read the first comments of every post that names a tracked term and return the comments that mention it too. Complaints, recommendations and comparisons are often in the replies. A comment that names no term itself can still qualify when its thread does and it talks about the product (matchType PARENT_CONTEXT). ## `maxPostsPerTerm` (type: `integer`): How many posts to scan for each brand, searched alias, competitor and keyword, per subreddit when subreddits are listed. Reddit's search stops at roughly 250 results per query, sort and time window. ## `maxCommentsPerPost` (type: `integer`): How many comments to read in each thread, top comments first. ## `timeRange` (type: `string`): Only posts from this window. Use DAY or HOUR for scheduled monitoring. ## `sort` (type: `string`): Reddit's search ordering. NEW is right for monitoring; RELEVANCE, TOP and COMMENTS find the strongest or busiest matches across the whole window. ## `onlyNewMentions` (type: `boolean`): For scheduled monitoring: return (and charge for) only mentions this monitor has not delivered before. Memory is kept per monitor key in a named key-value store on your account. ## `monitorKey` (type: `string`): A name for this monitor's memory, e.g. notion-brand-monitor. Use the same key on every scheduled run. Without one, a key is derived from your terms and subreddits, so changing them starts a fresh memory. Setting a key with only-new mode off still records what was delivered, so rows show whether a mention is new. ## `baselineMode` (type: `string`): What the FIRST run of a new monitor key does in only-new mode. RETURN_CURRENT returns the current mentions in the time window. BASELINE_ONLY remembers them without returning or charging any, so the next run returns only mentions that appear after it. ## `minimumRelevance` (type: `integer`): Drop mentions below this relevance score (0–100). A brand named in a post title with product words nearby scores 75+; a plain mention 40; a lowercase common word with nothing product-like nearby ("an apple") 20; a search result whose body could not be read 15. Raise it for ambiguous brand names. ## `excludeWords` (type: `array`): Drop any post or comment containing one of these words or phrases, e.g. "apple pie", "linear algebra". ## `excludeAuthors` (type: `array`): Reddit usernames to leave out: your brand account, employees, known bots or promoters. u/name and name both work. ## `includeSentiment` (type: `boolean`): POSITIVE / NEUTRAL / NEGATIVE / MIXED and a score from -1 to +1, read from the sentences that name the term. Rule-based and inferred: treat it as a signal, not a verdict. ## `includeMentionCategory` (type: `boolean`): primaryCategory and secondaryCategories: COMPLAINT, PRAISE, BUG_REPORT, SUPPORT_ISSUE, FEATURE_REQUEST, COMPARISON, ALTERNATIVE_REQUEST, SWITCHING_INTENT, PURCHASE_INTENT, RECOMMENDATION, PRODUCT_FEEDBACK, QUESTION, CAMPAIGN_MENTION, GENERAL_MENTION. ## `includeIntent` (type: `boolean`): signals (SWITCHING_INTENT, ALTERNATIVE_REQUEST, COMPARISON_INTENT, SUPPORT_INTENT, RECOMMENDATION_INTENT, CANCEL_OR_CHURN_INTENT, FEATURE_REQUEST, BUYING_INTENT) and the switchingIntent flag. ## `includeBuyingIntent` (type: `boolean`): buyingIntent: true when the writer is considering buying, subscribing or upgrading ("should I get Notion Plus?", "is it worth it?"). ## `includeVelocitySummary` (type: `boolean`): Add observedMentionVelocity to the run summary: mentions in the last hour / 24 hours / 7 days, and per-term counts of new, positive, negative, complaint, comparison and purchase-intent mentions. ## `proxyConfiguration` (type: `object`): Apify Datacenter proxy (the default) or no proxy. Apify Residential is refused: the run fails at start. To route through your own residential provider, use Custom proxy URLs. ## `maxConcurrency` (type: `integer`): Searches and comment threads processed in parallel. Reddit paces each IP; higher values mostly help with many terms. ## `debugMode` (type: `boolean`): Write every evaluated post and comment, kept or dropped, with its relevance breakdown and matched phrases, to the DEBUG_MENTIONS record. ## Actor input object example ```json { "brands": [ "Notion" ], "aliases": { "Notion": [ "notion.so", "notion app" ] }, "competitors": [], "keywords": [], "subreddits": [], "searchCompetitors": true, "scanPosts": true, "scanComments": true, "maxPostsPerTerm": 100, "maxCommentsPerPost": 50, "timeRange": "WEEK", "sort": "NEW", "onlyNewMentions": false, "baselineMode": "RETURN_CURRENT", "minimumRelevance": 30, "excludeWords": [], "excludeAuthors": [], "includeSentiment": true, "includeMentionCategory": true, "includeIntent": true, "includeBuyingIntent": true, "includeVelocitySummary": true, "proxyConfiguration": { "useApifyProxy": true }, "maxConcurrency": 3, "debugMode": false } ``` # Actor output Schema ## `mentions` (type: `string`): One row per unique post or comment mentioning a tracked term, most relevant first. ## `signals` (type: `string`): Sentiment, category, intent signals, competitors and the phrases that triggered them. ## `relevance` (type: `string`): Matched terms, aliases, match type and the point-by-point relevance breakdown. ## `runSummary` (type: `string`): Posts and comments scanned, new vs already-seen mentions, sentiment and category counts, observed mention velocity, cost per mention. ## `sourceSummary` (type: `string`): Status of every term and subreddit search (SUCCESS, NO_RESULTS, BLOCKED …). # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "brands": [ "Notion" ], "aliases": { "Notion": [ "notion.so", "notion app" ] }, "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("coregent/reddit-brand-mention-monitor").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "brands": ["Notion"], "aliases": { "Notion": [ "notion.so", "notion app", ] }, "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("coregent/reddit-brand-mention-monitor").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "brands": [ "Notion" ], "aliases": { "Notion": [ "notion.so", "notion app" ] }, "proxyConfiguration": { "useApifyProxy": true } }' | apify call coregent/reddit-brand-mention-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,coregent/reddit-brand-mention-monitor" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/pgexw9EeI7pNHVn5f/builds/8uUeMuMIR09jtq0Gn/openapi.json