Industry Solutions

In an era of information overload, the media and public relations industry faces unprecedented challenges. LargitData InfoMiner's real-time sentiment analysis system helps you accurately monitor brand sentiment volume, track issue trends, and respond at the first moment of a crisis — all from the hundreds of thousands of online data points generated every day.

Industry Challenges

Modern media and PR professionals must contend with enormous volumes of news coverage, social media posts, and forum discussions every day. Traditional manual monitoring is not only time-consuming and labor-intensive — it also struggles to detect breaking crisis events at the earliest possible moment. The following are the core pain points currently facing the media and public relations industry:

• Information Overload：Millions of pieces of online content are generated every day, making it impossible for human teams to comprehensively monitor all relevant coverage and discussions.
• Crisis Response Speed：Negative sentiment can spread across social media within hours; without real-time detection, the optimal window for response will be missed.
• Difficulty Integrating Across Platforms：News websites, Facebook, PTT, YouTube, Instagram, forums, and other platforms all use different data formats, making unified analysis difficult.
• Insufficient Tracking of Competitor Activity：Without systematic tools, it is difficult to continuously monitor competitors' media exposure and brand strategies.
• Lack of Data for KOL Partnership Evaluation：When selecting influencers or key opinion leaders for partnerships, objective influence data and audience analytics are lacking.

Industry Solutions

LargitData InfoMiner's real-time sentiment analysis system is purpose-built for the media and public relations industry, delivering comprehensive online sentiment monitoring and AI analytics capabilities:

• Real-Time Monitoring of Over 500,000 Channels：InfoMiner integrates over 500,000 data sources — including news websites, social media, forums, and blogs — ensuring that no important information is missed.
• AI Sentiment Analysis Engine：Leveraging NLP technology, InfoMiner automatically identifies the positive or negative sentiment of articles, precisely measuring the trajectory of brand reputation.
• Real-Time Alert Notifications：When abnormal volume spikes or the eruption of a negative issue is detected, the system instantly sends alerts via email and SMS, enabling the PR team to activate its response at the earliest possible moment.
• Visual Dashboard：Intuitive visual reports — including volume trend charts, keyword clouds, and source distribution maps — help teams rapidly understand the full picture of public sentiment.
• Automated Daily and Weekly Reports：The system automatically generates media monitoring analysis reports, saving PR teams significant manual compilation time.

Learn more about InfoMiner features:InfoMiner Social Listening

Diverse application scenarios

Scenario 1: Real-Time Brand Crisis Detection and Response

A well-known consumer brand used InfoMiner to detect in real time that a negative exposé post on PTT was spreading rapidly. The system sent an alert within 15 minutes of the post being published, and the PR team immediately activated its crisis management process, completing the official response before the issue reached news headlines and successfully containing the negative impact to a minimum.

Scenario 2: Competitor Media Strategy Tracking

A PR agency used InfoMiner to simultaneously monitor its client brand and five major competitors' online sentiment volume. By leveraging AI to automatically analyze competitors' media coverage frequency, reporting themes, and sentiment tone, the agency produced weekly competitive analysis reports, helping clients refine their brand positioning and media strategy.

Scenario 3: KOL Influence Evaluation and Partnership ROI Tracking

Brand marketing teams use InfoMiner's social data analytics to evaluate the genuine influence, audience composition, and engagement quality of potential KOL partners. During campaigns, they continuously track the reach of KOL posts and the resulting changes in brand sentiment volume, using data to drive future KOL partnership decisions.

Scenario 4: New Product Launch Media Monitoring

Before and after a new product launch, marketing teams configure product keyword monitoring in InfoMiner to track real-time consumer discussion intensity, positive and negative reviews, and key areas of focus, feeding rapid insights back to the product team for strategy adjustments.

Scenario 5: Industry Issue Trend Analysis

Media research teams use InfoMiner to track long-term discussion trends, key opinion leaders, and sentiment trajectories for specific industry topics — such as ESG, AI, and the metaverse — providing the newsroom with data-driven story and topic recommendations.

Expected Outcomes

• Crisis Response Time Reduced by 80%：Reduced from traditional hours of manual discovery to automatic system alerts within 15 minutes.
• Report Production Efficiency Improved by 60%：Automated daily and weekly reports replace manual compilation, allowing teams to focus on strategic analysis.
• Monitoring Coverage Expanded to 100%：Expanded from previously monitoring only major media outlets to comprehensive coverage of over 500,000 channels.
• More Precise Brand Reputation Management：AI sentiment analysis accuracy exceeds 90%, effectively quantifying brand image change trends.
• KOL Partnership ROI Improved by 40%：Data-driven KOL selection and performance tracking significantly improve marketing return on investment.