{"workflow":{"id":13653,"name":"Monitor brand mentions with OpenAI across Twitter/X, Reddit, News, Airtable and Slack","views":96,"recentViews":1,"totalViews":96,"createdAt":"2026-02-24T11:44:11.912Z","description":"Monitors brand mentions across Twitter/X, Reddit, and News APIs in real-time (or scheduled), fetches mentions in parallel, normalizes data, uses AI to analyze sentiment/urgency/topics, detects duplicates, filters critical mentions, logs everything to Airtable, posts alerts to Slack, and emails daily HTML digest reports to the marketing team.\n\n## Good to Know\n- Runs **every hour** (configurable) to provide near-real-time brand monitoring\n- Pulls mentions from **multiple platforms** in parallel: Twitter/X, Reddit, News sources\n- Uses **AI** (OpenAI/Grok/etc.) for advanced sentiment classification, urgency detection, topic extraction, and duplicate deduplication\n- Focuses on **actionable insights**: flags negative/urgent mentions for immediate response\n- Generates **beautiful HTML daily digest** with summarized mentions, sentiment trends, and key highlights\n- Stores historical data in **Airtable** for tracking, analytics, and long-term reporting\n- Sends **real-time Slack alerts** for high-priority/negative mentions\n- Reduces manual social monitoring time dramatically and helps catch reputation issues early\n\n## How It Works\n\n### 1. Trigger & configure\n- **Schedule Trigger** — Runs every hour (or custom interval) to check for new brand mentions\n- **Set brand monitoring config** — Defines brand name, keywords, excluded terms, monitoring parameters (via Set node or variables)\n\n### 2. Fetch & collect mentions\n- **Fetch Twitter/X mentions** — Uses Twitter/X node or HTTP Request to search recent tweets (mentions, keywords)\n- **Fetch Reddit mentions** — Searches relevant subreddits or Reddit-wide for brand keywords/posts\n- **Fetch news article mentions** — Queries news APIs (e.g. NewsAPI, Google News via RSS/HTTP) for brand coverage\n- **Merge platform mentions** — Combines results from all sources into a unified stream\n- **Normalize mentions into unified schema** — Standardizes fields (text, author, platform, timestamp, URL, etc.) for consistent processing\n\n### 3. AI analyze & deduplicate\n- **AI sentiment and urgency analysis** — Sends mentions to AI model (OpenAI node) with prompt to classify:\n - Sentiment: positive / neutral / negative\n - Urgency/severity: low / medium / high / critical\n - Topics/themes\n - Key excerpts\n- **Wait For Result** — Ensures AI responses are complete\n- **Process analysis results** — Parses structured JSON output from AI\n- **Filter mentions requiring alerts** — Routes based on sentiment/urgency thresholds\n- **Deduplicate** — Removes near-duplicate mentions (e.g. same content reposted)\n\n### 4. Store, alert & report\n- **Log mention to Airtable** — Appends/updates records with full details, sentiment, AI analysis, timestamp\n- **Route by sentiment and urgency** — Critical/negative → immediate action path\n- **Send mention alert** — Posts formatted message to **Slack** (or Discord/Teams) with link, text snippet, sentiment badge\n- **Generate HTML daily digest report** — Compiles summary: total mentions, sentiment breakdown, top issues, trends\n- **Email HTML digest** — Sends polished report to marketing team via **Email** node (SMTP/Gmail)\n- **Log success and update listings** — Records workflow completion, stats for monitoring\n\n## Data Sources\n- **Twitter/X** — Recent search for mentions/keywords (via Twitter node or HTTP Request with API)\n- **Reddit** — Subreddit or site-wide search for brand mentions\n- **News APIs** — NewsAPI.org, Google News RSS, or similar for article mentions\n- **AI Model** — OpenAI (GPT-4o / GPT series), Grok, or other LLM for sentiment/urgency analysis\n- **Storage** — Airtable base (tables for mentions, daily summaries)\n- **Notifications** — Slack (webhook or app), Email (SMTP)\n\n## How to Use\n1. **Import** the workflow JSON into your n8n instance\n2. **Configure credentials**:\n - Twitter/X API (OAuth or Bearer token for search)\n - Reddit API (if using official; or RSS/HTTP for subreddits)\n - News API key (e.g. NewsAPI.org)\n - OpenAI API key (or Grok/other LLM)\n - Airtable API key + base/table\n - Slack webhook or app token\n - Email SMTP credentials\n3. **Set monitoring parameters** — Edit brand name, keywords, exclude lists in **Set monitoring config** node\n4. **Customize AI prompt** — In the **AI sentiment** node, tweak for brand-specific tone, industry terms, urgency criteria\n5. **Adjust schedule** — Change interval in **Monitor mentions every hour** trigger\n6. **Tune filters** — Set thresholds for alerts (e.g. only negative + high urgency)\n7. **Test manually** — Use Execute Workflow to simulate with known mentions\n8. **Activate** — Turn on and watch Executions + Airtable/Slack for results\n\n## Requirements\n- n8n instance (self-hosted or cloud)\n- API access/keys for Twitter/X, Reddit (optional), News source\n- OpenAI (or compatible LLM) API key with good token limit\n- Airtable workspace/base for logging\n- Slack workspace for alerts\n- Email account for daily digests\n\n## Customizing This Workflow\n- **Add more platforms** — Include Facebook/Instagram (via Meta API), LinkedIn, Discord mentions\n- **Enhance AI analysis** — Add topic clustering, competitor comparison, virality scoring\n- **Improve deduplication** — Use fuzzy matching or embeddings for better duplicate detection\n- **Visual dashboard** — Export Airtable data to Google Looker Studio / Grafana for sentiment trends\n- **Auto-response** — For low-risk positive mentions, generate draft replies\n- **Language support** — Add multilingual sentiment detection\n- **Hourly vs. real-time** — Switch to webhook triggers if platforms support (e.g. Twitter webhooks if available)\n- **Daily/weekly reports** — Aggregate more stats, charts in HTML email\n\n","workflow":{"id":"am1RwBADxjmSSZRZ","meta":{"instanceId":"dd69efaf8212c74ad206700d104739d3329588a6f3f8381a46a481f34c9cc281","templateCredsSetupCompleted":true},"name":"AI Social Listening Agent","tags":[],"nodes":[{"id":"7c80824c-f381-4551-a857-74c7cd35337d","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[-2752,-464],"parameters":{"width":820,"height":720,"content":"## AI Social Listening Agent\n\nMonitors brand mentions across Twitter/X, Reddit, and news sources in real-time. Uses AI to analyze sentiment (positive/negative/neutral), detects trending topics, classifies urgency, and delivers actionable insights via Slack and Email with daily digest reports.\n\n## How it works\n\n1. **Trigger** — Runs every hour to check for new brand mentions\n2. **Fetch & collect** — Pulls mentions from Twitter/X, Reddit, and News APIs in parallel\n3. **Analyze** — AI sentiment analysis, urgency classification, and trend detection\n4. **Deduplicate** — Filters already-processed mentions to avoid noise\n5. **Alert** — Sends real-time Slack alerts for negative/urgent mentions; logs all to Airtable\n6. **Report** — Generates daily HTML digest and emails summary to marketing team\n\n## Setup steps\n\n1. **Social APIs** — Add your Twitter/X Bearer Token, Reddit Client ID/Secret, and News API Key\n2. **OpenAI** — Add your OpenAI API key for sentiment analysis\n3. **Airtable** — Create a `brand_mentions` base and add your API key\n4. **Slack** — Add your incoming webhook URL to the Slack node\n5. **Email** — Configure SMTP credentials and set `from` / `to` addresses\n6. **Brand Config** — Update the brand name and keywords in the Config node\n7. **Test** — Run manually to verify all connections, then activate"},"typeVersion":1},{"id":"43b61124-1746-4b60-9632-91ef576a8de4","name":"Sticky Note1","type":"n8n-nodes-base.stickyNote","position":[-1840,-368],"parameters":{"color":5,"width":468,"height":465,"content":"## 1. Trigger & configure\n\nRuns every hour to initiate brand monitoring. Config node sets brand name, keywords, and monitoring parameters"},"typeVersion":1},{"id":"875435b7-441a-46b2-a86f-1ccfced6b2a3","name":"Sticky Note2","type":"n8n-nodes-base.stickyNote","position":[-1328,-496],"parameters":{"color":5,"width":668,"height":820,"content":"## 2. Fetch & collect mentions\n\nFetches brand mentions from Twitter/X, Reddit, and News APIs in parallel, then merges all results into a unified stream"},"typeVersion":1},{"id":"67f60b4a-55fc-4e5e-9200-2553a772f960","name":"Sticky Note3","type":"n8n-nodes-base.stickyNote","position":[-624,-544],"parameters":{"color":5,"width":588,"height":905,"content":"## 3. AI analyze & deduplicate\n\nUses OpenAI to classify sentiment, detect urgency, extract topics, and deduplicates mentions already seen this session"},"typeVersion":1},{"id":"62d00e40-ad6e-458e-8ef6-13793c17d173","name":"Sticky Note4","type":"n8n-nodes-base.stickyNote","position":[32,-528],"parameters":{"color":5,"width":1328,"height":713,"content":"## 4. Store, alert & report\n\nLogs all mentions to Airtable, sends real-time Slack alerts for negative/urgent mentions, and emails a daily HTML digest to the marketing team"},"typeVersion":1},{"id":"28fbfdd8-4086-47b1-a30d-eaf8b80d5d54","name":"Monitor brand mentions every hour","type":"n8n-nodes-base.scheduleTrigger","position":[-1712,-64],"parameters":{"rule":{"interval":[{"field":"hours"}]}},"typeVersion":1.2},{"id":"39123f7b-7809-4887-bdf8-9105af94f0f7","name":"Set brand monitoring config","type":"n8n-nodes-base.set","position":[-1488,-64],"parameters":{"options":{},"assignments":{"assignments":[{"id":"brand-name","name":"brandName","type":"string","value":"YourBrand"},{"id":"keywords","name":"keywords","type":"string","value":"YourBrand,@YourBrand,#YourBrand"},{"id":"lookback-hours","name":"lookbackHours","type":"number","value":1},{"id":"alert-threshold","name":"negativeAlertThreshold","type":"number","value":3}]}},"typeVersion":3.4},{"id":"dbac966d-a71b-4dc9-84b3-621beca97b98","name":"Fetch Twitter/X mentions","type":"n8n-nodes-base.httpRequest","position":[-1264,-352],"parameters":{"url":"https://api.twitter.com/2/tweets/search/recent","options":{},"sendQuery":true,"sendHeaders":true,"queryParameters":{"parameters":[{"name":"query","value":"={{ $json.brandName + ' -is:retweet lang:en' }}"},{"name":"tweet.fields","value":"created_at,author_id,text,public_metrics,geo"},{"name":"max_results","value":"50"}]},"headerParameters":{"parameters":[{"name":"Authorization","value":"Bearer YOUR_TOKEN_HERE"}]}},"typeVersion":4.2},{"id":"f3a1d9e5-14e8-4b1c-a04c-57a23f5cd2a4","name":"Fetch Reddit mentions","type":"n8n-nodes-base.httpRequest","position":[-1264,-160],"parameters":{"url":"https://www.reddit.com/search.json","options":{},"sendQuery":true,"queryParameters":{"parameters":[{"name":"q","value":"={{ $json.brandName }}"},{"name":"sort","value":"new"},{"name":"t","value":"day"},{"name":"limit","value":"25"}]}},"typeVersion":4.2},{"id":"d6f98d40-927b-41b0-bd18-5246780b10b8","name":"Fetch news article mentions","type":"n8n-nodes-base.httpRequest","position":[-1264,32],"parameters":{"url":"https://newsapi.org/v2/everything","options":{},"sendQuery":true,"queryParameters":{"parameters":[{"name":"q","value":"={{ $json.brandName }}"},{"name":"sortBy","value":"publishedAt"},{"name":"language","value":"en"},{"name":"pageSize","value":"20"},{"name":"apiKey","value":"YOUR_NEWS_API_KEY"}]}},"typeVersion":4.2},{"id":"0a3f264c-b449-41de-822f-888ac8b0e899","name":"Merge all platform mentions","type":"n8n-nodes-base.merge","position":[-1040,-160],"parameters":{"mode":"combine","options":{}},"typeVersion":3},{"id":"81837c5d-634f-4019-8195-46fc6268d41c","name":"Normalize mentions into unified schema","type":"n8n-nodes-base.code","position":[-816,-160],"parameters":{"jsCode":"// Normalize all platform data into a unified mention schema\nconst items = $input.all();\nconst normalizedMentions = [];\nconst now = new Date();\nconst brandName = 'YourBrand'; // Update to match config\n\nitems.forEach(item => {\n const data = item.json;\n\n // Twitter/X mentions\n if (data.data && Array.isArray(data.data)) {\n data.data.forEach(tweet => {\n normalizedMentions.push({\n platform: 'Twitter/X',\n mentionId: `tw_${tweet.id}`,\n text: tweet.text || '',\n author: tweet.author_id || 'unknown',\n url: `https://twitter.com/i/web/status/${tweet.id}`,\n publishedAt: tweet.created_at || now.toISOString(),\n likes: tweet.public_metrics?.like_count || 0,\n shares: tweet.public_metrics?.retweet_count || 0,\n reach: (tweet.public_metrics?.like_count || 0) + (tweet.public_metrics?.retweet_count || 0),\n rawData: tweet\n });\n });\n }\n\n // Reddit mentions\n if (data.data?.children && Array.isArray(data.data.children)) {\n data.data.children.forEach(post => {\n const p = post.data;\n normalizedMentions.push({\n platform: 'Reddit',\n mentionId: `rd_${p.id}`,\n text: `${p.title} ${p.selftext || ''}`.trim(),\n author: p.author || 'unknown',\n url: `https://reddit.com${p.permalink}`,\n publishedAt: new Date(p.created_utc * 1000).toISOString(),\n likes: p.score || 0,\n shares: p.num_comments || 0,\n reach: p.score || 0,\n rawData: p\n });\n });\n }\n\n // News mentions\n if (data.articles && Array.isArray(data.articles)) {\n data.articles.forEach((article, idx) => {\n normalizedMentions.push({\n platform: 'News',\n mentionId: `nw_${Buffer.from(article.url || idx.toString()).toString('base64').slice(0,12)}`,\n text: `${article.title} ${article.description || ''}`.trim(),\n author: article.source?.name || 'Unknown Source',\n url: article.url || '',\n publishedAt: article.publishedAt || now.toISOString(),\n likes: 0,\n shares: 0,\n reach: 0,\n rawData: article\n });\n });\n }\n});\n\nconst reportTimestamp = now.toISOString();\nconst reportDate = now.toLocaleDateString('en-US', { year: 'numeric', month: 'long', day: 'numeric' });\n\nreturn normalizedMentions.map(mention => ({\n json: {\n ...mention,\n brandName,\n reportTimestamp,\n reportDate,\n totalMentionsCollected: normalizedMentions.length\n }\n}));"},"typeVersion":2},{"id":"c5e986df-9285-4d2b-b43f-4ea0f4569d8d","name":"AI sentiment and urgency analysis","type":"n8n-nodes-base.httpRequest","position":[-592,-160],"parameters":{"url":"https://api.openai.com/v1/chat/completions","method":"POST","options":{},"jsonBody":"={\n \"model\": \"gpt-4o-mini\",\n \"max_tokens\": 300,\n \"response_format\": { \"type\": \"json_object\" },\n \"messages\": [\n {\n \"role\": \"system\",\n \"content\": \"You are a brand monitoring AI. Analyze the given text and return ONLY valid JSON with these fields: sentiment (positive/negative/neutral), sentimentScore (-1.0 to 1.0), urgency (low/medium/high/critical), topics (array of up to 3 key topics), summary (one sentence), requiresResponse (boolean), language (ISO 639-1 code).\"\n },\n {\n \"role\": \"user\",\n \"content\": \"Analyze this brand mention from {{ $json.platform }}: {{ $json.text }}\"\n }\n ]\n}","sendBody":true,"sendHeaders":true,"specifyBody":"json","headerParameters":{"parameters":[{"name":"Authorization","value":"Bearer YOUR_TOKEN_HERE"},{"name":"Content-Type","value":"application/json"}]}},"typeVersion":4.2},{"id":"11463390-874b-43e1-ab29-1b5dc31f4b76","name":"Process AI analysis results","type":"n8n-nodes-base.code","position":[-160,-160],"parameters":{"mode":"runOnceForEachItem","jsCode":"// Parse AI response and enrich mention with sentiment data\nconst item = $input.item.json;\n\nlet aiAnalysis = {};\ntry {\n const content = item.choices?.[0]?.message?.content || '{}';\n aiAnalysis = JSON.parse(content);\n} catch (e) {\n aiAnalysis = {\n sentiment: 'neutral',\n sentimentScore: 0,\n urgency: 'low',\n topics: [],\n summary: 'Analysis unavailable',\n requiresResponse: false,\n language: 'en'\n };\n}\n\nconst sentiment = aiAnalysis.sentiment || 'neutral';\nconst urgency = aiAnalysis.urgency || 'low';\n\n// Generate mention ID for dedup tracking\nconst mentionId = item.mentionId || `gen_${Date.now()}`;\n\n// Check duplicate via static data\nconst processedMentions = $getWorkflowStaticData('global').processedMentions || {};\nconst isDuplicate = !!processedMentions[mentionId];\n\nif (!isDuplicate) {\n processedMentions[mentionId] = {\n timestamp: new Date().toISOString(),\n sentiment,\n urgency\n };\n // Clean up mentions older than 7 days\n const sevenDaysAgo = Date.now() - (7 * 24 * 60 * 60 * 1000);\n for (const key in processedMentions) {\n if (new Date(processedMentions[key].timestamp).getTime() < sevenDaysAgo) {\n delete processedMentions[key];\n }\n }\n $getWorkflowStaticData('global').processedMentions = processedMentions;\n}\n\n// Update cumulative stats\nconst stats = $getWorkflowStaticData('global').mentionStats || {\n total: 0, positive: 0, negative: 0, neutral: 0, critical: 0, byPlatform: {}\n};\nif (!isDuplicate) {\n stats.total++;\n if (sentiment === 'positive') stats.positive++;\n else if (sentiment === 'negative') stats.negative++;\n else stats.neutral++;\n if (urgency === 'critical') stats.critical++;\n stats.byPlatform[item.platform] = (stats.byPlatform[item.platform] || 0) + 1;\n $getWorkflowStaticData('global').mentionStats = stats;\n}\n\nconst requiresAlert = (sentiment === 'negative' && urgency !== 'low') || urgency === 'critical';\n\nreturn {\n json: {\n ...item,\n mentionId,\n sentiment,\n sentimentScore: aiAnalysis.sentimentScore || 0,\n urgency,\n topics: aiAnalysis.topics || [],\n aiSummary: aiAnalysis.summary || '',\n requiresResponse: aiAnalysis.requiresResponse || false,\n language: aiAnalysis.language || 'en',\n isDuplicate,\n requiresAlert,\n processedAt: new Date().toISOString()\n }\n};"},"typeVersion":2},{"id":"d74607a5-73b7-48ae-90fa-5ef7f0b2722c","name":"Route by sentiment and urgency","type":"n8n-nodes-base.switch","position":[64,-176],"parameters":{"rules":{"values":[{"outputKey":"Critical — Immediate Alert","conditions":{"options":{"leftValue":"","caseSensitive":true,"typeValidation":"strict"},"combinator":"and","conditions":[{"operator":{"type":"string","operation":"equals"},"leftValue":"={{ $json.urgency }}","rightValue":"critical"}]},"renameOutput":true},{"outputKey":"Negative — Needs Attention","conditions":{"options":{"leftValue":"","caseSensitive":true,"typeValidation":"strict"},"combinator":"and","conditions":[{"operator":{"type":"string","operation":"equals"},"leftValue":"={{ $json.sentiment }}","rightValue":"negative"}]},"renameOutput":true},{"outputKey":"Positive or Neutral","conditions":{"options":{"leftValue":"","caseSensitive":true,"typeValidation":"strict"},"combinator":"or","conditions":[{"operator":{"type":"string","operation":"equals"},"leftValue":"={{ $json.sentiment }}","rightValue":"positive"},{"operator":{"type":"string","operation":"equals"},"leftValue":"={{ $json.sentiment }}","rightValue":"neutral"}]},"renameOutput":true}]},"options":{}},"typeVersion":3},{"id":"56f4a0f6-87ae-48b3-8c63-356a4938a057","name":"Send critical mention alert","type":"n8n-nodes-base.httpRequest","position":[288,-352],"parameters":{"url":"https://api.example.com/alerts/send","method":"POST","options":{},"sendBody":true,"sendHeaders":true,"bodyParameters":{"parameters":[{"name":"alert_type","value":"CRITICAL_BRAND_MENTION"},{"name":"severity","value":"critical"},{"name":"platform","value":"={{ $json.platform }}"},{"name":"mention_id","value":"={{ $json.mentionId }}"},{"name":"sentiment","value":"={{ $json.sentiment }}"},{"name":"message","value":"={{ 'CRITICAL brand mention on ' + $json.platform + ': ' + $json.aiSummary + ' — URL: ' + $json.url }}"}]},"headerParameters":{"parameters":[{"name":"Content-Type","value":"application/json"}]}},"typeVersion":4.2},{"id":"bcc14722-99ac-42a7-8558-63db38e82b2c","name":"Log mention to Airtable","type":"n8n-nodes-base.httpRequest","position":[288,-160],"parameters":{"url":"https://api.airtable.com/v0/YOUR_BASE_ID/brand_mentions","method":"POST","options":{},"jsonBody":"={\n \"fields\": {\n \"Mention ID\": \"{{ $json.mentionId }}\",\n \"Platform\": \"{{ $json.platform }}\",\n \"Text\": \"{{ $json.text.slice(0, 500) }}\",\n \"Author\": \"{{ $json.author }}\",\n \"URL\": \"{{ $json.url }}\",\n \"Sentiment\": \"{{ $json.sentiment }}\",\n \"Sentiment Score\": {{ $json.sentimentScore }},\n \"Urgency\": \"{{ $json.urgency }}\",\n \"Topics\": \"{{ $json.topics.join(', ') }}\",\n \"AI Summary\": \"{{ $json.aiSummary }}\",\n \"Requires Response\": {{ $json.requiresResponse }},\n \"Published At\": \"{{ $json.publishedAt }}\",\n \"Processed At\": \"{{ $json.processedAt }}\",\n \"Is Duplicate\": {{ $json.isDuplicate }},\n \"Reach\": {{ $json.reach }}\n }\n}","sendBody":true,"sendHeaders":true,"specifyBody":"json","headerParameters":{"parameters":[{"name":"Authorization","value":"Bearer YOUR_TOKEN_HERE"},{"name":"Content-Type","value":"application/json"}]}},"typeVersion":4.2},{"id":"06e26387-1dc9-46c9-9af2-41b4f73509fb","name":"Generate HTML daily digest report","type":"n8n-nodes-base.code","position":[512,-240],"parameters":{"mode":"runOnceForEachItem","jsCode":"// Generate HTML daily digest report for brand mentions\nconst mention = $input.item.json;\nconst stats = $getWorkflowStaticData('global').mentionStats || { total: 0, positive: 0, negative: 0, neutral: 0, critical: 0, byPlatform: {} };\n\nconst sentimentColor = mention.sentiment === 'positive' ? '#22c55e' : mention.sentiment === 'negative' ? '#ef4444' : '#94a3b8';\nconst urgencyColor = mention.urgency === 'critical' ? '#ef4444' : mention.urgency === 'high' ? '#f97316' : mention.urgency === 'medium' ? '#f59e0b' : '#22c55e';\nconst sentimentIcon = mention.sentiment === 'positive' ? '😊' : mention.sentiment === 'negative' ? '😠' : '😐';\n\nconst platformRows = Object.entries(stats.byPlatform).map(([p, count]) => `${p}${count}`).join('') || 'No data yet';\n\nconst positiveRate = stats.total > 0 ? Math.round((stats.positive / stats.total) * 100) : 0;\nconst negativeRate = stats.total > 0 ? Math.round((stats.negative / stats.total) * 100) : 0;\nconst neutralRate = stats.total > 0 ? Math.round((stats.neutral / stats.total) * 100) : 0;\n\nconst reportHtml = `\n\n\n\n \n Brand Mention Digest — ${mention.reportDate}\n \n\n\n
\n

📡 Brand Social Listening Digest

\n

Brand: ${mention.brandName}  |  Report Date: ${mention.reportDate}  |  Platforms: Twitter/X, Reddit, News

\n
${sentimentIcon} Latest: ${mention.sentiment?.toUpperCase()}
\n
\n\n
\n
${stats.total}
Total Mentions
\n
${positiveRate}%
Positive Sentiment
\n
${negativeRate}%
Negative Sentiment
\n
${stats.critical}
Critical Alerts
\n
\n\n
\n

📊 Sentiment Breakdown

\n \n \n \n \n
SentimentCountRate
✅ Positive${stats.positive}${positiveRate}%
❌ Negative${stats.negative}${negativeRate}%
😐 Neutral${stats.neutral}${neutralRate}%
\n
\n\n
\n

🌐 Mentions by Platform

\n ${platformRows}
PlatformMentions
\n
\n\n
\n

🔔 Latest Mention

\n
\n ${mention.platform} — ${mention.sentiment?.toUpperCase()}  |  Urgency: ${mention.urgency?.toUpperCase()}
\n

${mention.aiSummary || mention.text?.slice(0, 200)}

\n Topics: ${(mention.topics || []).join(', ') || 'N/A'}  |  Author: ${mention.author}  |  View Original\n
\n
\n\n
Automated report generated by AI Social Listening Agent  |  ${mention.processedAt}
\n\n`;\n\nconst notificationMessage = `${sentimentIcon} *BRAND MENTION — ${mention.platform}*\\n\\n` +\n `*Brand:* ${mention.brandName}\\n` +\n `*Sentiment:* ${mention.sentiment?.toUpperCase()} (${mention.sentimentScore > 0 ? '+' : ''}${mention.sentimentScore?.toFixed(2)})\\n` +\n `*Urgency:* ${mention.urgency?.toUpperCase()}\\n` +\n `*Summary:* ${mention.aiSummary}\\n` +\n `*Topics:* ${(mention.topics || []).join(', ') || 'N/A'}\\n` +\n `*Author:* ${mention.author}\\n` +\n `*Platform:* ${mention.platform}\\n` +\n `*URL:* ${mention.url}\\n\\n` +\n `*Session Stats:* ${stats.total} mentions | ${positiveRate}% positive | ${negativeRate}% negative`;\n\nreturn {\n json: {\n ...mention,\n reportHtml,\n notificationMessage,\n notificationTitle: `${sentimentIcon} [${mention.platform}] ${mention.sentiment?.toUpperCase()} brand mention — ${mention.urgency?.toUpperCase()} urgency`,\n shouldAlert: mention.requiresAlert || mention.urgency === 'critical',\n sessionStats: stats\n }\n};"},"typeVersion":2},{"id":"f146210a-6a32-406e-8798-8a779df66147","name":"Filter mentions requiring alerts","type":"n8n-nodes-base.filter","position":[736,-240],"parameters":{"options":{},"conditions":{"options":{"leftValue":"","caseSensitive":false,"typeValidation":"strict"},"combinator":"and","conditions":[{"id":"alert-filter","operator":{"type":"boolean","operation":"true"},"leftValue":"={{ $json.shouldAlert }}"}]}},"typeVersion":2},{"id":"72fb1a15-ce54-48cb-bd79-7e78689bc5dc","name":"Post mention alert to Slack","type":"n8n-nodes-base.httpRequest","position":[960,-256],"parameters":{"url":"YOUR_SLACK_WEBHOOK_URL","method":"POST","options":{},"jsonBody":"={\n \"text\": \"{{ $json.notificationTitle }}\",\n \"blocks\": [\n {\n \"type\": \"section\",\n \"text\": {\n \"type\": \"mrkdwn\",\n \"text\": \"{{ $json.notificationMessage }}\"\n }\n }\n ]\n}","sendBody":true,"specifyBody":"json"},"typeVersion":4.2},{"id":"64a6aa14-c229-45c8-b818-f245f8868bbd","name":"Email HTML digest to marketing 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json: {\n success: true,\n mentionId: mention.mentionId,\n platform: mention.platform,\n sentiment: mention.sentiment,\n urgency: mention.urgency,\n requiresResponse: mention.requiresResponse,\n isDuplicate: mention.isDuplicate,\n alertSent: mention.shouldAlert,\n timestamp,\n sessionStats: {\n totalMentions: stats.total || 0,\n positiveCount: stats.positive || 0,\n negativeCount: stats.negative || 0,\n neutralCount: stats.neutral || 0,\n criticalAlerts: stats.critical || 0,\n byPlatform: stats.byPlatform || {}\n }\n }\n};"},"typeVersion":2},{"id":"a9cc90cf-9c9c-481a-afc2-67af5d0de035","name":"Wait For Result","type":"n8n-nodes-base.wait","position":[-384,-160],"webhookId":"ffce5ead-b7b9-45ee-890e-20ca241fa867","parameters":{},"typeVersion":1.1}],"active":false,"pinData":{},"settings":{"executionOrder":"v1"},"versionId":"7a1be7c0-e86e-4a4c-9003-f703640dd3bf","connections":{"Wait For Result":{"main":[[{"node":"Process AI analysis results","type":"main","index":0}]]},"Fetch Reddit 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