{ "name": "Case 62 - Industry Influencer Sentiment Tracker", "nodes": [ { "parameters": { "rule": { "interval": [ { "field": "cronExpression", "expression": "0 9 * * 1" } ] } }, "type": "n8n-nodes-base.scheduleTrigger", "typeVersion": 1.2, "position": [ -1008, -80 ], "id": "8fe930b1-441d-49e9-a0d1-b20a535165c1", "name": "Weekly Schedule - Monday 9 AM" }, { "parameters": { "actorId": { "__rl": true, "value": "buIWk2uOUzTmcLsuB", "mode": "list", "cachedResultName": "Linkedin Post Search Scraper (No Cookies) (harvestapi/linkedin-post-search)", "cachedResultUrl": "https://console.apify.com/actors/buIWk2uOUzTmcLsuB/input" }, "customBody": "{\n \"authorUrls\": [\n \"https://www.linkedin.com/in/andrew-ng\",\n \"https://www.linkedin.com/in/pascal-bornet\",\n \"https://www.linkedin.com/in/alliekmiller\",\n \"https://www.linkedin.com/in/bernardmarr\",\n \"https://www.linkedin.com/in/cassie-kozyrkov\"\n ],\n \"maxPosts\": 20,\n \"maxReactions\": 5,\n \"postedLimit\": \"month\",\n \"scrapeComments\": false,\n \"scrapeReactions\": false\n}" }, "type": "@apify/n8n-nodes-apify.apify", "typeVersion": 1, "position": [ -816, -80 ], "id": "8d7beeba-7127-4e69-84c0-825e58f1802c", "name": "Scrape LinkedIn Influencer Posts", "credentials": { "apifyApi": { "id": "w5S6YBbbyUddEfQA", "name": "Apify account" } } }, { "parameters": { "resource": "Datasets", "datasetId": "={{ $json.defaultDatasetId }}", "limit": 100 }, "type": "@apify/n8n-nodes-apify.apify", "typeVersion": 1, "position": [ -608, -80 ], "id": "023846f7-f027-4611-8303-32c8aa9b568e", "name": "Get Dataset Items", "credentials": { "apifyApi": { "id": "w5S6YBbbyUddEfQA", "name": "Apify account" } } }, { "parameters": { "conditions": { "options": { "caseSensitive": true, "leftValue": "", "typeValidation": "strict", "version": 1 }, "conditions": [ { "id": "condition-001", "leftValue": "={{ $json.content }}", "rightValue": "AI automation", "operator": { "type": "string", "operation": "contains" } }, { "id": "condition-002", "leftValue": "={{ $json.content }}", "rightValue": "intelligent automation", "operator": { "type": "string", "operation": "contains" } }, { "id": "condition-003", "leftValue": "={{ $json.content }}", "rightValue": "workflow automation", "operator": { "type": "string", "operation": "contains" } }, { "id": "condition-004", "leftValue": "={{ $json.content }}", "rightValue": "AI agents", "operator": { "type": "string", "operation": "contains" } }, { "id": "condition-005", "leftValue": "={{ $json.content }}", "rightValue": "process automation", "operator": { "type": "string", "operation": "contains" } }, { "id": "condition-006", "leftValue": "={{ $json.content }}", "rightValue": "automation strategy", "operator": { "type": "string", "operation": "contains" } } ], "combinator": "or" }, "options": {} }, "type": "n8n-nodes-base.filter", "typeVersion": 2, "position": [ -400, -80 ], "id": "4b968876-8f40-410c-81fa-f5a59297fba9", "name": "Filter AI Automation Keywords" }, { "parameters": { "modelId": { "__rl": true, "value": "gpt-4o-mini", "mode": "list", "cachedResultName": "GPT-4o-mini" }, "responses": { "values": [ { "role": "system", "content": "=You are an AI Sentiment Analysis Expert specializing in LinkedIn influencer content analysis.\n\nExtract sentiment and key insights from LinkedIn posts about AI automation.\n\nReturn ONLY valid JSON in this exact format:\n{\n \"sentiment\": \"positive|negative|neutral\",\n \"confidence_score\": 0.85,\n \"stance\": \"supportive|critical|balanced|neutral\",\n \"key_arguments\": [\"argument 1\", \"argument 2\", \"argument 3\"],\n \"emotional_tone\": \"professional|passionate|cautious|critical|optimistic|concerned\",\n \"topic_category\": \"AI automation|intelligent automation|workflow automation|AI agents|process automation|automation strategy\",\n \"business_implications\": \"brief description of mentioned business/policy impacts or null\"\n}\n\nRules:\n1. sentiment must be one of: positive, negative, neutral\n2. confidence_score between 0 and 1 (how confident you are in sentiment assessment)\n3. stance captures overall position on the topic\n4. Extract maximum 3 key arguments - the main points being made\n5. emotional_tone captures the writing style and emotion\n6. topic_category must match one of the provided categories\n7. business_implications: summarize any mentioned impact on business, policy, or industry (1 sentence max)\n8. Return ONLY the JSON object, no explanations" }, { "content": "=Analyze this LinkedIn post for sentiment and key insights:\n\nAuthor: {{ $json.author.name }}\nPost Date: {{ $json.postedAt.date }}\nPost Text: {{ $json.content }}\n\nReturn only JSON." } ] }, "builtInTools": {}, "options": {} }, "type": "@n8n/n8n-nodes-langchain.openAi", "typeVersion": 2.1, "position": [ -208, -80 ], "id": "349098fd-f524-487b-8be8-e7c575d711b5", "name": "AI Sentiment Analysis", "credentials": { "openAiApi": { "id": "ICwxUBbatsF2sDvy", "name": "OpenAi account" } } }, { "parameters": { "operation": "append", "documentId": { "__rl": true, "value": "1GLjosJxue_mhpX_6FiEnhPDs__7kks2ivTSAuUsksCM", "mode": "list", "cachedResultName": "Case 62 - Influencer Sentiment Log", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1GLjosJxue_mhpX_6FiEnhPDs__7kks2ivTSAuUsksCM/edit?usp=drivesdk" }, "sheetName": { "__rl": true, "value": "gid=0", "mode": "list", "cachedResultName": "Sheet1", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1GLjosJxue_mhpX_6FiEnhPDs__7kks2ivTSAuUsksCM/edit#gid=0" }, "columns": { "mappingMode": "defineBelow", "value": { "Analysis_Date": "={{ $json.analysis_timestamp }}", "Influencer_Name": "={{ $json.influencer_name }}", "Post_Date": "={{ $json.post_date }}", "Topic_Category": "={{ $json.topic_category }}", "Sentiment": "={{ $json.sentiment }}", "Confidence_Score": "={{ $json.confidence_score }}", "Stance": "={{ $json.stance }}", "Emotional_Tone": "={{ $json.emotional_tone }}", "Key_Arguments": "={{ $json.key_arguments.join('; ') }}", "Business_Implications": "={{ $json.business_implications }}", "Likes": "={{ $json.likes_count }}", "Comments": "={{ $json.comments_count }}", "Shares": "={{ $json.shares_count }}", "Total_Engagement": "={{ $json.engagement_total }}", "Post_URL": "={{ $json.post_url }}", "Post_Text": "={{ $json.post_text }}" }, "matchingColumns": [], "schema": [ { "id": "Analysis_Date", "displayName": "Analysis_Date", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Influencer_Name", "displayName": "Influencer_Name", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Post_Date", "displayName": "Post_Date", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Topic_Category", "displayName": "Topic_Category", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Sentiment", "displayName": "Sentiment", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Confidence_Score", "displayName": "Confidence_Score", "required": false, "defaultMatch": false, "display": true, "type": "number", "canBeUsedToMatch": true }, { "id": "Stance", "displayName": "Stance", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Emotional_Tone", "displayName": "Emotional_Tone", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Key_Arguments", "displayName": "Key_Arguments", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Business_Implications", "displayName": "Business_Implications", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Likes", "displayName": "Likes", "required": false, "defaultMatch": false, "display": true, "type": "number", "canBeUsedToMatch": true }, { "id": "Comments", "displayName": "Comments", "required": false, "defaultMatch": false, "display": true, "type": "number", "canBeUsedToMatch": true }, { "id": "Shares", "displayName": "Shares", "required": false, "defaultMatch": false, "display": true, "type": "number", "canBeUsedToMatch": true }, { "id": "Total_Engagement", "displayName": "Total_Engagement", "required": false, "defaultMatch": false, "display": true, "type": "number", "canBeUsedToMatch": true }, { "id": "Post_URL", "displayName": "Post_URL", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Post_Text", "displayName": "Post_Text", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true } ] }, "options": {} }, "type": "n8n-nodes-base.googleSheets", "typeVersion": 4.7, "position": [ 512, -80 ], "id": "12028bc0-904a-44db-b50d-83237a5bdaef", "name": "Log to Google Sheet", "credentials": { "googleSheetsOAuth2Api": { "id": "LOs2dbk9lby0NfDM", "name": "Google Sheets account" } } }, { "parameters": { "jsCode": "// Aggregate all items from Google Sheets into email-ready summary\nconst allItems = $input.all();\n\n// Calculate sentiment breakdown\nconst sentimentCounts = { positive: 0, negative: 0, neutral: 0 };\nallItems.forEach(item => {\n const sentiment = (item.json.Sentiment || 'neutral').toLowerCase();\n if (sentimentCounts.hasOwnProperty(sentiment)) {\n sentimentCounts[sentiment]++;\n }\n});\n\nconst totalPosts = allItems.length;\nconst sentimentPercentages = {\n positive: Math.round((sentimentCounts.positive / totalPosts) * 100),\n negative: Math.round((sentimentCounts.negative / totalPosts) * 100),\n neutral: Math.round((sentimentCounts.neutral / totalPosts) * 100)\n};\n\n// Find trending arguments (most mentioned)\n// Key_Arguments is now a string like \"arg1; arg2; arg3\"\nconst argumentCounts = {};\nallItems.forEach(item => {\n const argsString = item.json.Key_Arguments || '';\n if (argsString) {\n const args = argsString.split(';').map(arg => arg.trim()).filter(arg => arg);\n args.forEach(arg => {\n argumentCounts[arg] = (argumentCounts[arg] || 0) + 1;\n });\n }\n});\n\nconst trendingArguments = Object.entries(argumentCounts)\n .sort((a, b) => b[1] - a[1])\n .slice(0, 5)\n .map(([arg, count]) => ({ argument: arg, mentions: count }));\n\n// Top influencers by engagement\nconst influencerEngagement = {};\nallItems.forEach(item => {\n const name = item.json.Influencer_Name || 'Unknown';\n if (!influencerEngagement[name]) {\n influencerEngagement[name] = { total: 0, posts: 0 };\n }\n influencerEngagement[name].total += parseInt(item.json.Total_Engagement || 0);\n influencerEngagement[name].posts++;\n});\n\nconst topInfluencers = Object.entries(influencerEngagement)\n .map(([name, data]) => ({\n name,\n avg_engagement: Math.round(data.total / data.posts),\n total_posts: data.posts\n }))\n .sort((a, b) => b.avg_engagement - a.avg_engagement)\n .slice(0, 5);\n\n// Build HTML table rows for detailed posts\nconst tableRows = allItems.map(item => {\n const data = item.json;\n const sentiment = data.Sentiment || 'neutral';\n const sentimentColor = sentiment.toLowerCase() === 'positive' ? '#28a745' : \n sentiment.toLowerCase() === 'negative' ? '#dc3545' : '#6c757d';\n \n return `\n \n ${data.Influencer_Name || 'N/A'}\n ${data.Post_Date || 'N/A'}\n ${sentiment}\n ${data.Stance || 'N/A'}\n ${(parseInt(data.Total_Engagement || 0)).toLocaleString()}\n View\n \n `;\n}).join('');\n\n// Return single aggregated item\nreturn {\n json: {\n week_start: new Date(Date.now() - 7*24*60*60*1000).toISOString().split('T')[0],\n week_end: new Date().toISOString().split('T')[0],\n total_posts_analyzed: totalPosts,\n sentiment_positive_pct: sentimentPercentages.positive,\n sentiment_negative_pct: sentimentPercentages.negative,\n sentiment_neutral_pct: sentimentPercentages.neutral,\n trending_arguments: trendingArguments,\n top_influencers: topInfluencers,\n table_rows: tableRows,\n all_posts: allItems.map(item => item.json)\n }\n};" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 720, -80 ], "id": "16c2965c-cede-4013-bd9e-3a9eb8d2dff1", "name": "Aggregate Weekly Summary" }, { "parameters": { "sendTo": "strategy-team@yourcompany.com", "subject": "=📊 Weekly AI Automation Sentiment Report: {{ $json.week_start }} to {{ $json.week_end }}", "message": "=\n\n \n\n\n
\n \n
\n

📊 Weekly AI Automation Sentiment Report

\n

{{ $json.week_start }} to {{ $json.week_end }}

\n
\n \n
\n

📈 Sentiment Overview

\n
\n
{{ $json.total_posts_analyzed }}
\n
Posts Analyzed
\n
\n \n
\n
\n
\n
\n
\n \n
\n ● Positive: {{ $json.sentiment_positive_pct }}%   \n ● Neutral: {{ $json.sentiment_neutral_pct }}%   \n ● Negative: {{ $json.sentiment_negative_pct }}%\n
\n
\n \n
\n

🔥 Trending Arguments This Week

\n \n
\n \n
\n

👥 Top Influencers by Engagement

\n {{ $json.top_influencers.map((inf, index) => `\n
\n ${index + 1}. ${inf.name}\n
\n Avg Engagement: ${inf.avg_engagement.toLocaleString()}  |  \n Posts: ${inf.total_posts}\n
\n
\n `).join('') }}\n
\n \n

📋 Detailed Post Analysis

\n \n \n \n \n \n \n \n \n \n \n \n \n {{ $json.table_rows }}\n \n
InfluencerDateSentimentStanceEngagementLink
\n \n
\n

Report Generated: {{ new Date().toLocaleString() }}

\n

Automated Influencer Sentiment Tracker | Case 62

\n
\n \n
\n\n", "options": {} }, "type": "n8n-nodes-base.gmail", "typeVersion": 2.1, "position": [ 912, -80 ], "id": "64814542-281c-46cf-9c28-7253f1f3b9fa", "name": "Send Weekly Summary Email", "webhookId": "d2ab0ef3-3f3c-49ef-852b-45a82730634c", "credentials": { "gmailOAuth2": { "id": "cyqCGWcggZNMcSOv", "name": "Gmail account" } } }, { "parameters": { "jsCode": "// UNIVERSAL AI RESPONSE PARSER - Same code for ALL cases\nconst items = [];\nconst input = $input.all();\n\nfunction extractJSON(text) {\n const jsonMatch = text.match(/\\{[\\s\\S]*\\}/);\n if (!jsonMatch) return null;\n return jsonMatch[0];\n}\n\ninput.forEach((item, index) => {\n try {\n let aiText = item.json.output[0].content[0].text || '';\n \n // Clean markdown code blocks\n aiText = aiText\n .replace(/```json/gi, '')\n .replace(/```/g, '')\n .trim();\n \n // Extract JSON object\n const jsonStr = extractJSON(aiText);\n \n if (!jsonStr) {\n throw new Error('No JSON found in AI response');\n }\n \n // Parse and return clean JSON\n const parsed = JSON.parse(jsonStr);\n items.push({ json: parsed });\n \n } catch (error) {\n console.error(`Parse error for item ${index}:`, error.message);\n // Return empty object on error - no case-specific fields\n items.push({ json: {} });\n }\n});\n\nreturn items;" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 112, -80 ], "id": "72dc27b5-bdc8-4e87-a06a-c5a89ce1a95e", "name": "Parse AI Response" }, { "parameters": { "assignments": { "assignments": [ { "id": "timestamp", "name": "analysis_timestamp", "value": "={{ new Date().toISOString() }}", "type": "string" }, { "id": "influencer_name", "name": "influencer_name", "value": "={{ $('Filter AI Automation Keywords').item.json.author?.name || 'unknown' }}", "type": "string" }, { "id": "influencer_profile", "name": "influencer_profile", "value": "={{ $('Filter AI Automation Keywords').item.json.author?.linkedinUrl || '' }}", "type": "string" }, { "id": "post_text", "name": "post_text", "value": "={{ $('Filter AI Automation Keywords').item.json.content || '' }}", "type": "string" }, { "id": "post_date", "name": "post_date", "value": "={{ $('Filter AI Automation Keywords').item.json.postedAt?.date || '' }}", "type": "string" }, { "id": "post_url", "name": "post_url", "value": "={{ $('Filter AI Automation Keywords').item.json.linkedinUrl || '' }}", "type": "string" }, { "id": "sentiment", "name": "sentiment", "value": "={{ $json.sentiment }}", "type": "string" }, { "id": "confidence", "name": "confidence_score", "value": "={{ $json.confidence_score }}", "type": "number" }, { "id": "stance", "name": "stance", "value": "={{ $json.stance }}", "type": "string" }, { "id": "arguments", "name": "key_arguments", "value": "={{ $json.key_arguments }}", "type": "array" }, { "id": "tone", "name": "emotional_tone", "value": "={{ $json.emotional_tone }}", "type": "string" }, { "id": "category", "name": "topic_category", "value": "={{ $json.topic_category }}", "type": "string" }, { "id": "implications", "name": "business_implications", "value": "={{ $json.business_implications }}", "type": "string" }, { "id": "likes", "name": "likes_count", "value": "={{ $('Filter AI Automation Keywords').item.json.engagement?.likes || 0 }}", "type": "number" }, { "id": "comments", "name": "comments_count", "value": "={{ $('Filter AI Automation Keywords').item.json.engagement?.comments || 0 }}", "type": "number" }, { "id": "shares", "name": "shares_count", "value": "={{ $('Filter AI Automation Keywords').item.json.engagement?.shares || 0 }}", "type": "number" }, { "id": "total_engagement", "name": "engagement_total", "value": "={{ ($('Filter AI Automation Keywords').item.json.engagement?.likes || 0) + ($('Filter AI Automation Keywords').item.json.engagement?.comments || 0) + ($('Filter AI Automation Keywords').item.json.engagement?.shares || 0) }}", "type": "number" } ] }, "options": {} }, "type": "n8n-nodes-base.set", "typeVersion": 3.4, "position": [ 336, -80 ], "id": "a71301da-bba5-41ba-99ab-14c8967e512c", "name": "Edit Fields" } ], "pinData": {}, "connections": { "Weekly Schedule - Monday 9 AM": { "main": [ [ { "node": "Scrape LinkedIn Influencer Posts", "type": "main", "index": 0 } ] ] }, "Scrape LinkedIn Influencer Posts": { "main": [ [ { "node": "Get Dataset Items", "type": "main", "index": 0 } ] ] }, "Get Dataset Items": { "main": [ [ { "node": "Filter AI Automation Keywords", "type": "main", "index": 0 } ] ] }, "Filter AI Automation Keywords": { "main": [ [ { "node": "AI Sentiment Analysis", "type": "main", "index": 0 } ] ] }, "AI Sentiment Analysis": { "main": [ [ { "node": "Parse AI Response", "type": "main", "index": 0 } ] ] }, "Aggregate Weekly Summary": { "main": [ [ { "node": "Send Weekly Summary Email", "type": "main", "index": 0 } ] ] }, "Parse AI Response": { "main": [ [ { "node": "Edit Fields", "type": "main", "index": 0 } ] ] }, "Edit Fields": { "main": [ [ { "node": "Log to Google Sheet", "type": "main", "index": 0 } ] ] }, "Log to Google Sheet": { "main": [ [ { "node": "Aggregate Weekly Summary", "type": "main", "index": 0 } ] ] } }, "active": false, "settings": { "executionOrder": "v1" }, "versionId": "ea3dc47f-f957-45fc-9c6b-5f4ed3c2c0d2", "meta": { "templateCredsSetupCompleted": true, "instanceId": "3a43da28588548e21903e71cf1dc3ddd65c24bf0c62e7e4b77542ffe87ad79c6" }, "id": "fmJQjmsU8aABpExZ", "tags": [] }