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🧪 Beta Release - This tool is in Beta and actively being refined based on user feedback.

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Overview

The Sentiment Tearsheet provides real-time media sentiment analysis for public companies, delivering a comprehensive view of how the media perceives a company. This tool returns a markdown report with sentiment scores, media attention metrics, an AI-generated narrative summarizing sentiment drivers, and cited source articles supporting the analysis. This tool provides more complete and detailed sentiment analysis than the sentiment summary included in the Company tearsheet, making it ideal for in-depth sentiment research and monitoring.

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When to Use

The Sentiment Tearsheet is ideal for:
  • Sentiment analysis: Understanding whether media coverage is bullish, bearish, or neutral
  • Media perception tracking: Monitoring how the media views a company over time
  • News tone assessment: Gauging the overall tone of recent media coverage
  • Sentiment driver identification: Understanding what’s driving positive or negative media narratives
  • Media attention tracking: Monitoring how much media coverage a company is receiving
  • Investment research: Incorporating sentiment signals into fundamental analysis
  • Crisis monitoring: Tracking sentiment shifts during corporate events or controversies
  • Pre-earnings analysis: Gauging media sentiment heading into earnings releases

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How It Works

The Sentiment Tearsheet follows a multi-step process to ensure accurate company identification and sentiment retrieval:
  1. Call: A call is made to find_companies with company name, ticker, or identifier
  2. Extract: The id field is extracted (used as rp_entity_id)
  3. Call: A call is then made to bigdata_sentiment_tearsheet with the rp_entity_id
  4. Analysis: Real-time media coverage is analyzed to generate sentiment scores, narratives, and citations
This workflow ensures the correct company is identified before retrieving sentiment data.

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Coverage Limitations

  • Public companies only: Sentiment analysis is available for publicly traded companies
  • Recent media coverage required: Companies must have recent media coverage for sentiment analysis
  • If a company has insufficient recent coverage, the tool will indicate no data is available

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Data Returned

The Sentiment Tearsheet returns a comprehensive markdown report with the following components:

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1. Sentiment Score & Direction

Overall media sentiment classification:
  • Bullish: Predominantly positive media coverage (score > 0.5)
  • Neutral: Balanced or mixed media coverage (score between -0.5 and 0.5)
  • Bearish: Predominantly negative media coverage (score < -0.5)
Sentiment Score Range: -1.0 (extremely bearish) to +1.0 (extremely bullish)

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2. Media Attention Level

Volume of media coverage over recent periods:
  • 24-Hour Attention: Recent media activity and coverage intensity
  • Trending: Whether media attention is increasing, decreasing, or stable
  • Attention Context: How current coverage compares to historical baseline

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3. AI-Generated Narrative

A structured summary explaining the sentiment drivers:
  • Main Themes: Key topics driving sentiment (earnings, product launches, regulatory issues, management changes, etc.)
  • Positive Drivers: Specific factors contributing to bullish sentiment
  • Negative Drivers: Specific factors contributing to bearish sentiment
  • Context: Industry trends, competitive dynamics, or macro factors affecting perception
The narrative is generated by analyzing recent media coverage and identifying the most significant sentiment-driving themes.

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4. Cited Source Articles

Supporting evidence for the narrative:
  • Article Headlines: Titles of relevant news articles
  • Publication Sources: Media outlets publishing the coverage
  • Publication Dates: When the articles were published
  • Article Sentiment: Individual article tone (positive, neutral, negative)
  • Relevance: How strongly each article relates to the company
Citations provide transparency and allow users to verify sentiment drivers by reading source material.

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Understanding the Data

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Sentiment Score Interpretation

Strongly Bullish (+0.7 to +1.0):
  • Overwhelmingly positive media coverage
  • Often associated with major positive catalysts (strong earnings, breakthrough products, strategic wins)
  • High confidence in positive sentiment
Moderately Bullish (+0.3 to +0.7):
  • Mostly positive coverage with some neutral or mildly negative articles
  • Typical during stable growth periods or modest positive news
Neutral (-0.3 to +0.3):
  • Balanced or mixed coverage
  • May indicate quiet periods, conflicting news, or transitional phases
Moderately Bearish (-0.7 to -0.3):
  • Mostly negative coverage with some neutral or mildly positive articles
  • Often during challenges, controversies, or disappointing results
Strongly Bearish (-1.0 to -0.7):
  • Overwhelmingly negative media coverage
  • Associated with major negative events (scandals, regulatory action, earnings misses, layoffs)
  • High confidence in negative sentiment

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Media Attention Context

High Attention:
  • Company is generating significant media coverage
  • Often driven by major news events, earnings releases, or controversies
  • High attention with negative sentiment may indicate a potential crisis
  • High attention with positive sentiment suggests positive momentum
Low Attention:
  • Limited recent media coverage
  • May indicate quiet period between major events
  • Can be normal for stable, mature companies
Trending Up:
  • Media coverage is increasing
  • May indicate building story or emerging narrative
  • Sentiment direction alongside rising attention provides important context
Trending Down:
  • Media coverage is declining
  • Story may be losing relevance or has been resolved
  • Can be positive (controversy fading) or neutral (news cycle moving on)

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AI Narrative Quality

The AI-generated narrative synthesizes hundreds of articles into key themes:
  • Specificity: Focuses on concrete events and developments, not vague generalizations
  • Recency: Emphasizes the most recent coverage driving current sentiment
  • Balance: Acknowledges both positive and negative drivers when present
  • Context: Places sentiment in industry or market context

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Using Cited Sources

Citations serve multiple purposes:
  • Verification: Confirm the narrative accurately reflects source material
  • Deep Dive: Read full articles for comprehensive understanding
  • Source Quality: Assess credibility based on publication reputation
  • Timeliness: Check publication dates to ensure recency

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Use Cases

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Investment Research

Incorporate sentiment signals into fundamental analysis to identify potential catalysts or risks not yet reflected in price.

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Risk Monitoring

Track sentiment for portfolio holdings to detect emerging controversies or negative narratives before they impact stock price.

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Event Analysis

Analyze sentiment shifts around earnings releases, product launches, or corporate events to gauge market reaction.

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Competitive Intelligence

Compare sentiment across competitors to identify relative positioning and media narrative strength.

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Crisis Management

Monitor real-time sentiment during corporate crises to assess media narrative evolution and response effectiveness.

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Thematic Research

Identify companies benefiting from positive secular trends (AI adoption, clean energy transition) reflected in media sentiment.

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Contrarian Signals

Look for disconnect between sentiment and fundamentals - extreme bearish sentiment may signal oversold opportunities, extreme bullish may signal froth.

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Pre-Earnings Positioning

Gauge media sentiment and attention heading into earnings to assess expectations and potential surprise direction.

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Practical Tips

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Combining with Other Data

Sentiment + Financials:
  • Strong bullish sentiment + strong earnings = confirmed positive narrative
  • Strong bearish sentiment + strong earnings = potential sentiment turnaround opportunity
  • Sentiment improving + revenue growth accelerating = positive momentum
Sentiment + Price Action:
  • Bullish sentiment + stock declining = potential disconnect or lagging price
  • Bearish sentiment + stock rising = market may be looking past negative news
  • Sentiment and price aligned = narrative confirmed by market
Sentiment + Company tearsheet:
  • Cross-reference sentiment drivers with financial metrics (revenue, margins, guidance)
  • Verify narrative themes against actual business performance
  • Use analyst ratings alongside sentiment for comprehensive view

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Temporal Context Matters

  • Short-term sentiment spikes: Often driven by single events, may not reflect long-term narrative
  • Sustained sentiment shifts: More meaningful signal of changing perception
  • Sentiment volatility: High volatility may indicate controversial or polarizing developments

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Industry Context

  • Tech companies: Often have volatile sentiment driven by product cycles and innovation narratives
  • Financial companies: Sentiment heavily influenced by regulatory news and economic conditions
  • Consumer companies: Sentiment affected by brand perception, product quality, and social issues
  • Energy/Materials: Sentiment closely tied to commodity prices and environmental concerns

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Frequency of Monitoring

  • Daily: During earnings season, major events, or crisis situations
  • Weekly: For active portfolio management and tactical positioning
  • Monthly: For long-term fundamental research and strategic allocation

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Sentiment vs Company Tearsheet

Use Sentiment Tearsheet when:
  • Primary focus is understanding media perception and sentiment drivers
  • Need detailed narrative explaining what’s driving sentiment
  • Want to verify sentiment through cited source articles
  • Conducting in-depth sentiment analysis or monitoring
Use Company Tearsheet when:
  • Need comprehensive financial data alongside sentiment
  • Want a complete company overview (financials, analyst ratings, ESG, sentiment)
  • Sentiment is one of many data points in analysis
Both tools provide sentiment data, but the Sentiment Tearsheet offers deeper analysis with narratives and citations, while the Company Tearsheet provides sentiment as one component of a broader financial overview.