How to Use Google NotebookLM for AI-Driven Social Listening and Monitoring in 2025

Guest Lecture Context
This article is based on a professional training session where Jansen Lu, Independent Digital Marketing Consultant and Corporate Trainer, was invited as a guest speaker on 18 October 2024 for the Professional Certificate in AI-Driven Digital and Social Media Marketing course at PolyU SPEED, led by Dr. Ken FONG (Course Leader). During the lecture, Jansen demonstrated authentic, data-driven social-listening and crisis-monitoring workflows using Google NotebookLM, illustrating how AI can transform fragmented online discourse into structured brand intelligence.

Introduction — When Social Listening Becomes Intelligence

Traditional social-listening tools merely count mentions or visualize spikes. NotebookLM goes deeper—it reads, compares, and reasons across the material you provide. By grounding its AI output strictly in curated sources—news articles, social posts, transcripts, and videos—it delivers verifiable insights rather than hallucinated trends.

At PolyU SPEED, Jansen Lu guided participants through actual monitoring exercises involving crisis tracking, influencer sentiment analysis, and week-by-week narrative mapping. The examples below show how those demonstrations unfolded in real time.

Why NotebookLM Excels for Social Listening (2025 Edition)

The 2025 upgrade of NotebookLM Studio turns it into a full social-intelligence workspace. Its core modules work together to analyse, narrate, and visualise social data:

• Audio & Video Overviews — AI-generated briefings that narrate or animate evolving sentiment.
• Mind Map — clusters topics, voices, and emotions for instant pattern recognition.
• Reports — long-form analytical documents citing every source.
• Flashcards & Quiz — convert insights into team learning material.
• Google Workspace Sync — real-time collaborative editing and annotation.
• Multimodal Exports — combine text, visuals, and audio into one deliverable.

These capabilities make NotebookLM a one-stop hub for communications, PR, and marketing teams that need fast, traceable, and context-aware monitoring.

Prompts Used by Jansen (Live Demonstration)

• “List all public criticism themes (Category | Representative Quote | Source ID | Tone).” / 「請整理出評論類型、代表性留言、來源連結與情緒傾向。」
• “Compare organiser responses (Response | Adequacy ✓ / ✕ | Remaining Risk).” / 「列出主辦方的回應，並以表格方式評估是否解決對應問題。」
• “Identify which issues escalated after the first response.”
• “Show narrative shifts week-by-week using sources tagged ‘Week 1–3’.”
• “Generate a 90-second Audio Overview summarising the main public sentiment drivers.”

“Don’t just ask ‘what do people think’. Ask ‘who said what, when, and how did the brand reply?’ That’s when AI becomes analysis.” — Jansen Lu

Case Studies from the PolyU SPEED Workshop

Case 1 — The Travel Agency Crisis: 富國島交友團事件 (Phú Quốc Island Dating Tour Incident)

A Hong Kong travel company organised a dating-tour package to Phú Quốc Island (Vietnam). After participants complained online about sub-standard accommodation and refund disputes, the story went viral.

Data uploaded: five news articles and TV segments; the organiser’s public statements; dozens of participant posts and comments; YouTube clips with captions.

Prompts used: “Summarise all allegations and link each to the organiser’s reply (Table A).” “Assess whether responses address the actual pain points.” “List recurring narrative keywords (e.g., ‘不符宣傳’, ‘衞生問題’, ‘退款糾紛’).”

NotebookLM output: two structured tables—“Allegations ↔ Responses” and “Public vs Organiser Tone”; an Audio Overview narrating how the sentiment escalated from Day 1 rumours to mainstream media coverage.

Insight: By consolidating multiple interviews and posts, NotebookLM helped visualise the timeline of public outrage and pinpoint which organiser replies failed to match complaint themes—turning qualitative feedback into measurable accountability.

Case 2 — Retail Giveaway Backlash: 7-Eleven × Anime Collaboration

A limited-edition card giveaway between 7-Eleven and a popular anime brand triggered an online storm over fairness and exclusivity.

Data uploaded: 20+ social posts and comment threads; press articles and fan forum discussions; YouTube reaction videos with subtitles.

Prompts used: “Extract opposing viewpoints (Support | Criticism | Neutral | Example Quote | Source ID).” “Map stakeholders: fans, influencers, brand representatives.” “Generate a 90-second Audio Overview explaining sentiment drivers.”

NotebookLM output: a Mind Map highlighting factions—supportive collectors, angry fans, and brand defenders—and an Audio Overview summarising how early miscommunication shaped perceptions.

Insight: The case showed how NotebookLM could condense hundreds of comments into a voice-narrated brief, helping brand managers grasp tone and context in minutes instead of hours.

Case 3 — KOL Reaction Tracking on AI in Marketing

The session closed with a forward-looking case on how influencers discuss generative AI in their content.

Data uploaded: transcripts from three KOL interviews and panel discussions.

Prompts used: “Synthesise each KOL’s stance on AI adoption (Optimistic | Cautious | Critical).” “Quote representative lines with [S#] citations.” “Summarise convergence or divergence of viewpoints.”

NotebookLM output: a thematic report and sentiment timeline chart showing how opinions shifted from “AI as threat” to “AI as assistant.”

Insight: NotebookLM acted as a research partner—filtering long interviews into data-driven takeaways for trend analysis.

Extending Social Listening into Action

• Build FAQs from recurring public questions.
• Draft educational posts to clarify misconceptions.
• Use Audio Overviews as training briefs for customer-service teams.

AI isn’t the decision—it reveals what requires a decision.

Governance & Verification Best Practices

• Cite sources ([S#]) for audit trails.
• Save verified answers as Notes to prevent loss of context.
• Keep one notebook per incident or campaign.
• For sensitive data, use Google Drive sharing instead of public URLs.

Writer’s Insight — 2025 Perspective

NotebookLM has matured into a true social-intelligence workspace. The 2025 Studio update adds Video Overviews, multimodal exports, and Workspace collaboration—closing the loop between data and decision. For marketers, the future of social listening is a continuous cycle: curate → analyze → narrate → act. NotebookLM now makes that cycle simpler, faster, and auditable—an indispensable tool for AI-driven communication in 2025 and beyond.

References

• NotebookLM Use Cases – Jansen Lu Guest Lecture (PolyU SPEED, 18 Oct 2024)
• Google NotebookLM Help Center & Product Documentation (2025 Studio updates on Audio / Video Overviews and Workspace Sync)

Traditional Chinese Summary（繁體中文摘要，約 850 字）

2024 年 10 月 18 日，香港理工大學專業進修學院（PolyU SPEED）「AI-Driven Digital and Social Media Marketing 專業證書課程」課堂邀請 Jansen Lu 擔任嘉賓講者。Jansen 以實際示範展示了如何運用 Google NotebookLM 進行社群輿情監測（Social Listening）與危機分析，並即場示範以 AI 將分散的留言、報導與訪談內容，轉化為具邏輯與可驗證的洞察報告。

NotebookLM 是 Google 開發的「來源導向 AI 研究助理」。使用者可上傳 PDF、音訊、新聞稿、YouTube 影片、Google 文件等資料，系統會在 Notebook 內自動轉錄、比對與歸納，只依據使用者提供的來源進行推理，並以 [S#] 標示引用出處。這一特性讓 NotebookLM 成為品牌公關與市場監測的理想工具。

在講堂中，Jansen 以三個真實案例展示其應用流程：

（一）富國島交友團事件（Phú Quốc Island Dating Tour Incident）
此事件涉及一間旅遊公司舉辦越南富國島交友團後，被參加者投訴住宿衞生及退款問題。Jansen 將新聞報導、主辦方聲明、參加者留言及 YouTube 片段匯入 NotebookLM，並以指令：「列出所有投訴主題及對應回應」、「分析主辦方回應是否解決問題」、「統計常見字詞如 ‘不符宣傳’ ‘衞生問題’ ‘退款糾紛’」。NotebookLM 自動生成對照表及情緒時序 Audio Overview，幫助判斷哪類回應未能止息輿論。

（二）便利店聯名贈品爭議（7-Eleven × Anime Collaboration）
限定贈品活動引起收藏族與動漫迷的不滿。Jansen 匯入 20 餘篇社群貼文、媒體報導與 YouTube 評論影片，使用指令：「萃取支持／批評／中立觀點」、「繪製利害關係者地圖」、「生成 90 秒 Audio Overview 說明情緒來源」。NotebookLM 輸出 Mind Map 及語音摘要，讓管理層能於短時間掌握爭議重點。

（三）KOL 對 AI 行銷的觀點追蹤
Jansen 匯入三位 KOL 的訪談逐字稿，要求 NotebookLM 「整合三者立場（樂觀／審慎／批判）」、「引用代表性語句並附 [S#] 來源」。結果生成主題報告與情緒折線圖，清晰顯示觀點如何由「AI 威脅」轉為「AI 助力」。

除示範外，Jansen 亦強調了提問技巧的重要性。例如他常用的提示語包括：「請整理出評論類型、代表性留言、來源連結與情緒傾向」、「列出主辦方的回應並以表格方式評估是否解決對應問題」、「以週次顯示敘事變化並生成 Audio Overview 摘要」。他提醒學生：「不要只問 ‘大家怎樣想’，要問 ‘誰在何時說了甚麼、品牌怎樣回應’——這才是分析。」

Jansen 建議將 NotebookLM 產出的洞察直接應用於策略層面：將常見問題轉為 FAQ、將誤解轉為教育貼文、將 Audio Overview 用作培訓教材。這讓 AI 不只是資訊工具，而是決策前的思考助手。

2025 年版本的 NotebookLM 新增 Video Overview、多模態輸出及 Google Workspace 協作，同步整合分析、敘事與視覺化。從 富國島事件 到 便利店贈品風波，課堂實例證明 NotebookLM 可讓行銷人員在一個工作空間中完成「蒐集 → 分析 → 敘事 → 行動」的閉環流程，大幅提升效率與治理透明度。

正如 Dr. Ken FONG 在課後所總結：
「自 2024 以來，NotebookLM 已從筆記工具進化為社群智慧工作室。對行銷與公關專業而言，這是 AI 監測走向策略決策的關鍵轉折點。」