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자동화된 포럼 모니터링_via_Bright_data

고급

이것은AI분야의자동화 워크플로우로, 17개의 노드를 포함합니다.주로 Set, Code, Html, HttpRequest, GoogleSheets 등의 노드를 사용하며인공지능 기술을 결합하여 스마트 자동화를 구현합니다. Bright Data와 n8n을 사용하여 포럼 모니터링 자동화

사전 요구사항
  • 대상 API의 인증 정보가 필요할 수 있음
  • Google Sheets API 인증 정보
  • OpenAI API Key

카테고리

워크플로우 미리보기
노드 연결 관계를 시각적으로 표시하며, 확대/축소 및 이동을 지원합니다
워크플로우 내보내기
다음 JSON 구성을 복사하여 n8n에 가져오면 이 워크플로우를 사용할 수 있습니다
{
  "id": "hEt4K6p0NxH8EKdf",
  "meta": {
    "instanceId": "60046904b104f0f72b2629a9d88fe9f676be4035769f1f08dad1dd38a76b9480"
  },
  "name": "Automated_Forum_Monetering_via_Bright_data",
  "tags": [],
  "nodes": [
    {
      "id": "d46077f8-080f-4611-afd9-75b3c50fd912",
      "name": "OpenAI Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        3280,
        820
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4o-mini"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "8sEyPDkC5p4w4Jha",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "e8147cbd-97f6-40c3-84b3-2d30d10e7e04",
      "name": "주기적 실행",
      "type": "n8n-nodes-base.scheduleTrigger",
      "position": [
        1780,
        600
      ],
      "parameters": {
        "rule": {
          "interval": [
            {
              "triggerAtHour": 9
            }
          ]
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "e60c1249-dc44-46b9-b691-5329f58d7e41",
      "name": "검색 키워드 정의",
      "type": "n8n-nodes-base.set",
      "position": [
        2000,
        600
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "96c78660-315e-491f-8942-56dc4365c093",
              "name": "keyword",
              "type": "string",
              "value": "iPhone+16"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "fd3c6b86-2f82-4290-84cf-50627dc38fb7",
      "name": "Google 검색 결과",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        2240,
        600
      ],
      "parameters": {
        "url": "https://api.brightdata.com/request",
        "method": "POST",
        "options": {},
        "jsonBody": "={\n  \"zone\": \"n8n_unblocker\",\n  \"url\": \"https://www.google.com/search?q=site:quora.com+{{ $json.keyword }}\",\n  \"country\": \"us\",\n  \"format\": \"raw\",\n  \"headers\": {\n    \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64)\"\n  }\n}",
        "sendBody": true,
        "sendHeaders": true,
        "specifyBody": "json",
        "headerParameters": {
          "parameters": [
            {
              "name": "Authorization",
              "value": "Bearer API_KEY"
            }
          ]
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "edddbf94-87ed-4d59-9fed-4994dedc618d",
      "name": "Google HTML에서 링크 추출",
      "type": "n8n-nodes-base.html",
      "position": [
        2440,
        600
      ],
      "parameters": {
        "options": {},
        "operation": "extractHtmlContent",
        "extractionValues": {
          "values": [
            {
              "key": "Thread Titles",
              "cssSelector": "h3",
              "returnArray": true
            },
            {
              "key": "b",
              "cssSelector": "div.yuRUbf a",
              "returnArray": true,
              "returnValue": "attribute"
            }
          ]
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "2bb4b2c0-49a5-49e5-afc8-220d0e39d0ce",
      "name": "스레드 URL 형식화",
      "type": "n8n-nodes-base.code",
      "position": [
        2620,
        600
      ],
      "parameters": {
        "jsCode": "const titles = items[0].json[\"Thread Titles\"];\nconst urls = items[0].json[\"b\"].map(obj => obj.href);\n\n// Build array of { title, url }\nconst output = [];\n\nfor (let i = 0; i < Math.min(titles.length, urls.length); i++) {\n  output.push({\n    json: {\n      title: titles[i],\n      url: urls[i]\n    }\n  });\n}\n\nreturn output;\n"
      },
      "typeVersion": 2
    },
    {
      "id": "a3f3ad74-a548-4135-b07f-69f38bf7dd9b",
      "name": "개별 Quora 스레드",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        2860,
        600
      ],
      "parameters": {
        "url": "https://api.brightdata.com/request",
        "method": "POST",
        "options": {},
        "jsonBody": "={\n  \"zone\": \"n8n_unblocker\",\n  \"url\": \"{{ $json.url }}\",\n  \"country\": \"us\",\n  \"format\": \"raw\",\n  \"headers\": {\n    \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64)\"\n  }\n}",
        "sendBody": true,
        "sendHeaders": true,
        "specifyBody": "json",
        "headerParameters": {
          "parameters": [
            {
              "name": "Authorization",
              "value": "Bearer API_KEY"
            }
          ]
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "3c1de319-64fc-4cb8-b78f-92fbf0d7ecba",
      "name": "Google 시트에 저장",
      "type": "n8n-nodes-base.googleSheets",
      "position": [
        3660,
        600
      ],
      "parameters": {
        "columns": {
          "value": {
            "Topic": "={{ $('Define Search Keyword').item.json.keyword }}",
            "Discussion Summary": "={{ $json.output }}"
          },
          "schema": [
            {
              "id": "Topic",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Topic",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Discussion Summary",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Discussion Summary",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            }
          ],
          "mappingMode": "defineBelow",
          "matchingColumns": [],
          "attemptToConvertTypes": false,
          "convertFieldsToString": false
        },
        "options": {},
        "operation": "append",
        "sheetName": {
          "__rl": true,
          "mode": "list",
          "value": "gid=0",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1eCtVRklGjweUv7HS4wfMEGtdyd8YGzNl0D-3zNbExgM/edit#gid=0",
          "cachedResultName": "Sheet1"
        },
        "documentId": {
          "__rl": true,
          "mode": "list",
          "value": "1eCtVRklGjweUv7HS4wfMEGtdyd8YGzNl0D-3zNbExgM",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1eCtVRklGjweUv7HS4wfMEGtdyd8YGzNl0D-3zNbExgM/edit?usp=drivesdk",
          "cachedResultName": "Quora discussion summary"
        }
      },
      "credentials": {
        "googleSheetsOAuth2Api": {
          "id": "r2mDaisH6e9VkwHl",
          "name": "Google Sheets account"
        }
      },
      "typeVersion": 4.6
    },
    {
      "id": "efd597da-ed96-49b5-94d9-c5202e39eeca",
      "name": "AI 피드백 요약1",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        3300,
        600
      ],
      "parameters": {
        "text": "=Summarize the following consumer feedback from Quora:\n{{ $json.answers }}",
        "options": {},
        "promptType": "define"
      },
      "typeVersion": 2
    },
    {
      "id": "99bc2765-9f81-449c-9eac-9138aad22117",
      "name": "스레드에서 답변 추출",
      "type": "n8n-nodes-base.html",
      "position": [
        3080,
        600
      ],
      "parameters": {
        "options": {},
        "operation": "extractHtmlContent",
        "extractionValues": {
          "values": [
            {
              "key": "answers",
              "cssSelector": "=<span style=\"font-weight: normal; font-style: normal; background: none;\">Well, from what I know, it depends what you're hoping to get out of it . Like , honestly, if your 15 is working fine , why bother ? I mean , my brother just got the 15 and he's already talking about the 16 , it's crazy . He's always gotta have the newest thing, you know ? Waste of money, probably . Unless there's something *really* different, a game changer , a must-have feature.. . which there probably isnt, but marketing makes you think there is! I upgraded from a 13 to a 14, and honestly? Didn't notice much difference . The camera was *slightly* better, I guess , but not a huge jump. Maybe </span>",
              "returnArray": true
            }
          ]
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "e80004d6-b806-40cc-b91c-f04315a2cbf5",
      "name": "메모지",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1740,
        0
      ],
      "parameters": {
        "color": 5,
        "width": 420,
        "height": 780,
        "content": "### 🔹 **SECTION 1: Define and Trigger the Search**\n\n**🕒 Trigger + ✏️ Input Field**\n\n| Node | Name                           | Icon | Purpose                                                                                 |\n| ---- | ------------------------------ | ---- | --------------------------------------------------------------------------------------- |\n| 🕒   | `Trigger: Run Periodically`    | ⏰    | This node starts the workflow automatically based on a schedule (e.g., every 24 hours). |\n| ✏️   | `Input: Define Search Keyword` | 📝   | Manually input the product name or topic to monitor (e.g., \"iPhone 16\").                |\n\n#### 💡 Why it's useful:\n\nThis section ensures your automation runs regularly and searches for the **right product/topic** you’re interested in monitoring.\n\n---\n\n"
      },
      "typeVersion": 1
    },
    {
      "id": "875b5fef-45b8-494d-9984-252731491437",
      "name": "메모지1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        2180,
        40
      ],
      "parameters": {
        "color": 6,
        "width": 580,
        "height": 740,
        "content": "### 🔹 **SECTION 2: Scrape Quora Discussion Links via Google**\n\n**🌐 Scrape Google → 🧾 Extract Links → 🔧 Clean Links**\n\n| Node | Name                              | Icon | Purpose                                                                                   |\n| ---- | --------------------------------- | ---- | ----------------------------------------------------------------------------------------- |\n| 🌐   | `Scrape: Google Search Results`   | 🌍   | Performs a Google search using Bright Data's Web Unlocker (`site:quora.com {{keyword}}`). |\n| 📄   | `Extract: Links from Google HTML` | 🧩   | Extracts thread URLs from Google’s search result HTML using an HTML Extractor.            |\n| 🔧   | `Code: Format Thread URLs`        | 🛠️  | Cleans up and structures the extracted thread links into usable format for next steps.    |\n\n#### 💡 Why it's useful:\n\nThis part **finds actual Quora discussions** relevant to your keyword (like “iPhone 16”), even bypassing limitations like logins or anti-bot measures using Bright Data.\n\n---\n\n"
      },
      "typeVersion": 1
    },
    {
      "id": "198121dc-1955-4528-a4be-9f80b837e98c",
      "name": "메모지2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        2780,
        100
      ],
      "parameters": {
        "color": 3,
        "width": 440,
        "height": 680,
        "content": "### 🔹 **SECTION 3: Scrape Actual Quora Answers**\n\n**🌐 Scrape Threads → 📄 Extract Answer Content**\n\n| Node | Name                               | Icon | Purpose                                                   |\n| ---- | ---------------------------------- | ---- | --------------------------------------------------------- |\n| 🌐   | `Scrape: Individual Quora Threads` | 🌐   | Fetches full HTML of each Quora thread using Bright Data. |\n| 📄   | `Extract: Answers from Threads`    | 📑   | Extracts useful answers/comments from each thread’s HTML. |\n\n#### 💡 Why it's useful:\n\nThis section dives deep into each Quora thread and **extracts actual user feedback**, questions, and opinions — the real goldmine for consumer insights.\n\n---\n\n"
      },
      "typeVersion": 1
    },
    {
      "id": "8a48bc8d-18fc-4561-81dd-4bdb47118a29",
      "name": "메모지3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        3240,
        140
      ],
      "parameters": {
        "color": 2,
        "width": 580,
        "height": 800,
        "content": "### 🔹 **SECTION 4: Summarize & Store the Insights**\n\n**🤖 AI Summary → 📊 Google Sheet**\n\n| Node | Name                             | Icon | Purpose                                                                                        |\n| ---- | -------------------------------- | ---- | ---------------------------------------------------------------------------------------------- |\n| 🤖   | `Summarize: AI Feedback Summary` | 🤖   | Feeds all extracted text into OpenAI to generate a human-like summary of consumer feedback.    |\n| 📊   | `Store: Save to Google Sheet`    | 📈   | Saves the summarized output into Google Sheets for record-keeping, reporting, or team sharing. |\n\n#### 💡 Why it's useful:\n\nThis section **turns raw user opinions into actionable insights** and logs them automatically in a spreadsheet, making it easy for marketers, product teams, or analysts to access.\n\n---\n\n"
      },
      "typeVersion": 1
    },
    {
      "id": "afb12d4e-a33e-4075-af50-6baea9823663",
      "name": "메모지9",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        0,
        0
      ],
      "parameters": {
        "color": 4,
        "width": 1300,
        "height": 320,
        "content": "=======================================\n            WORKFLOW ASSISTANCE\n=======================================\nFor any questions or support, please contact:\n    Yaron@nofluff.online\n\nExplore more tips and tutorials here:\n   - YouTube: https://www.youtube.com/@YaronBeen/videos\n   - LinkedIn: https://www.linkedin.com/in/yaronbeen/\n=======================================\n"
      },
      "typeVersion": 1
    },
    {
      "id": "50dca867-69b8-4f76-a72f-4d528d721da0",
      "name": "메모지4",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        0,
        340
      ],
      "parameters": {
        "color": 4,
        "width": 1289,
        "height": 1958,
        "content": "## 🧠 **AUTOMATED FORUM MONITORING & INSIGHT GENERATOR**\n\n**Powered by Bright Data, n8n, OpenAI, and Google Sheets**\n\n---\n\n### 🔹 **SECTION 1: Define and Trigger the Search**\n\n**🕒 Trigger + ✏️ Input Field**\n\n| Node | Name                           | Icon | Purpose                                                                                 |\n| ---- | ------------------------------ | ---- | --------------------------------------------------------------------------------------- |\n| 🕒   | `Trigger: Run Periodically`    | ⏰    | This node starts the workflow automatically based on a schedule (e.g., every 24 hours). |\n| ✏️   | `Input: Define Search Keyword` | 📝   | Manually input the product name or topic to monitor (e.g., \"iPhone 16\").                |\n\n#### 💡 Why it's useful:\n\nThis section ensures your automation runs regularly and searches for the **right product/topic** you’re interested in monitoring.\n\n---\n\n### 🔹 **SECTION 2: Scrape Quora Discussion Links via Google**\n\n**🌐 Scrape Google → 🧾 Extract Links → 🔧 Clean Links**\n\n| Node | Name                              | Icon | Purpose                                                                                   |\n| ---- | --------------------------------- | ---- | ----------------------------------------------------------------------------------------- |\n| 🌐   | `Scrape: Google Search Results`   | 🌍   | Performs a Google search using Bright Data's Web Unlocker (`site:quora.com {{keyword}}`). |\n| 📄   | `Extract: Links from Google HTML` | 🧩   | Extracts thread URLs from Google’s search result HTML using an HTML Extractor.            |\n| 🔧   | `Code: Format Thread URLs`        | 🛠️  | Cleans up and structures the extracted thread links into usable format for next steps.    |\n\n#### 💡 Why it's useful:\n\nThis part **finds actual Quora discussions** relevant to your keyword (like “iPhone 16”), even bypassing limitations like logins or anti-bot measures using Bright Data.\n\n---\n\n### 🔹 **SECTION 3: Scrape Actual Quora Answers**\n\n**🌐 Scrape Threads → 📄 Extract Answer Content**\n\n| Node | Name                               | Icon | Purpose                                                   |\n| ---- | ---------------------------------- | ---- | --------------------------------------------------------- |\n| 🌐   | `Scrape: Individual Quora Threads` | 🌐   | Fetches full HTML of each Quora thread using Bright Data. |\n| 📄   | `Extract: Answers from Threads`    | 📑   | Extracts useful answers/comments from each thread’s HTML. |\n\n#### 💡 Why it's useful:\n\nThis section dives deep into each Quora thread and **extracts actual user feedback**, questions, and opinions — the real goldmine for consumer insights.\n\n---\n\n### 🔹 **SECTION 4: Summarize & Store the Insights**\n\n**🤖 AI Summary → 📊 Google Sheet**\n\n| Node | Name                             | Icon | Purpose                                                                                        |\n| ---- | -------------------------------- | ---- | ---------------------------------------------------------------------------------------------- |\n| 🤖   | `Summarize: AI Feedback Summary` | 🤖   | Feeds all extracted text into OpenAI to generate a human-like summary of consumer feedback.    |\n| 📊   | `Store: Save to Google Sheet`    | 📈   | Saves the summarized output into Google Sheets for record-keeping, reporting, or team sharing. |\n\n#### 💡 Why it's useful:\n\nThis section **turns raw user opinions into actionable insights** and logs them automatically in a spreadsheet, making it easy for marketers, product teams, or analysts to access.\n\n---\n\n## 🎁 **Benefits of This Workflow**\n\n✅ Automates tracking of online discussions around product launches\n✅ Bypasses anti-bot walls using Bright Data\n✅ Uses AI to summarize user feedback — no manual reading required\n✅ Saves results to Google Sheets for easy collaboration\n✅ Fully modular — change the topic anytime!\n\n---\n\n"
      },
      "typeVersion": 1
    },
    {
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      "name": "메모지5",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        3900,
        140
      ],
      "parameters": {
        "color": 7,
        "width": 380,
        "height": 240,
        "content": "## I’ll receive a tiny commission if you join Bright Data through this link—thanks for fueling more free content!\n\n### https://get.brightdata.com/1tndi4600b25"
      },
      "typeVersion": 1
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "f3426c3d-894c-4ba7-bb50-8ffc1f444bb7",
  "connections": {
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    "d46077f8-080f-4611-afd9-75b3c50fd912": {
      "ai_languageModel": [
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}
자주 묻는 질문

이 워크플로우를 어떻게 사용하나요?

위의 JSON 구성 코드를 복사하여 n8n 인스턴스에서 새 워크플로우를 생성하고 "JSON에서 가져오기"를 선택한 후, 구성을 붙여넣고 필요에 따라 인증 설정을 수정하세요.

이 워크플로우는 어떤 시나리오에 적합한가요?

고급 - 인공지능

유료인가요?

이 워크플로우는 완전히 무료이며 직접 가져와 사용할 수 있습니다. 다만, 워크플로우에서 사용하는 타사 서비스(예: OpenAI API)는 사용자 직접 비용을 지불해야 할 수 있습니다.

워크플로우 정보
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Yaron Been

Yaron Been

@yaron-nofluff

Building AI Agents and Automations | Growth Marketer | Entrepreneur | Book Author & Podcast Host If you need any help with Automations, feel free to reach out via linkedin: https://www.linkedin.com/in/yaronbeen/ And check out my Youtube channel: https://www.youtube.com/@YaronBeen/videos

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