TL;DR: Lens Score (0-100) identifies underreported news that matters. It measures: Coverage Gap (how underreported vs importance), Public Interest (how many people affected), Power Concentration (powerful institutions involved), and Accountability (evidence of failures/corruption). Higher score = more important but less covered. It's a "BS Detector in Reverse"—instead of filtering fake news, it surfaces real news being ignored.
In a media landscape where celebrity gossip often drowns out policy changes affecting millions, finding genuinely important news is harder than ever. Lens Score was designed to solve this problem.
The Problem: Important Stories Get Buried
Every day, Indian news outlets publish thousands of articles. But not all news gets equal coverage. Stories about powerful institutions, accountability failures, or systemic issues often receive less attention than entertainment or sensational content.
Consider: A minister's corruption case might get a single news cycle, while a celebrity wedding dominates headlines for weeks. A factory safety violation affecting thousands of workers might be reported by one outlet, while a viral tweet gets covered by dozens.
Lens Score identifies these underreported stories that deserve your attention.
What is Lens Score?
Lens Score is a 0-100 rating that identifies underreported news with high public interest. Unlike algorithms that chase virality, Lens Score finds important stories that mainstream media might be under-covering.
A high Lens Score (80+) means: "This story has significant public interest but isn't getting proportional media attention."
A low Lens Score (under 40) typically means: routine news, entertainment content, or stories already receiving adequate coverage.
How Lens Score Works
Our algorithm analyzes four key factors:
1. Public Interest Assessment (35% weight)
Not all news affects people equally. We evaluate:
Who is involved in wrongdoing?
- Government officials or politicians involved in misconduct score highest (these stories matter most for democracy)
- Law enforcement accountability issues receive high scores
- Corporate malfeasance affecting consumers or workers
- General incidents scale based on impact (number of people affected)
What's the impact?
- National policy changes affecting crores of citizens
- Public safety issues (infrastructure failures, health hazards)
- Rights violations and systemic discrimination
- Environmental damage affecting communities
What type of news is it?
- Hard news and investigative reports receive full weight
- Analysis and announcements receive moderate weight
- Opinion pieces and routine updates receive reduced weight
- Entertainment gossip and celebrity news receive minimal weight
2. Coverage Gap Analysis (30% weight)
This is where Lens Score differs from traditional "importance" metrics. We identify stories that aren't getting proportional coverage.
When a story has high public interest but low media attention, the coverage gap is high. These are exactly the stories that need to be surfaced.
We calculate this by comparing:
- How important the story appears to be (based on content analysis)
- How much coverage it's actually receiving across our 50+ monitored sources
A major corruption scandal covered by only 2-3 outlets has a high coverage gap. A celebrity interview covered by 40 outlets has a low coverage gap.
3. Power Entity Concentration (20% weight)
Stories involving powerful institutions often face coverage challenges. We identify:
- Government entities: Ministries, departments, PSUs, regulatory bodies
- Corporate entities: Major companies, business groups, industry bodies
- Political entities: Parties, elected officials, political organizations
- Enforcement agencies: Police, CBI, ED, NIA, military
- Judiciary: Courts, tribunals, judicial decisions
- Religious institutions: Organizations with significant influence
When multiple powerful entities are involved in a story, it often signals importance—and sometimes explains why coverage might be limited.
4. Accountability Indicators (15% weight)
We scan for red flags that indicate stories of public accountability:
- Financial irregularity: Fraud, embezzlement, corruption, benami transactions
- Abuse of power: Misuse of official position, nepotism, conflict of interest
- Systemic failure: Institutional breakdown, negligence, repeated failures
- Cover-up signals: Evidence destruction, obstruction, false statements
- Public safety issues: Health hazards, infrastructure dangers, contamination
- Rights violations: Illegal detention, discrimination, police brutality
- Electoral issues: Vote buying, EVM concerns, misuse of government machinery
- Environmental violations: Pollution, deforestation, illegal construction
Stories with multiple accountability indicators receive score boosts—these are exactly the stories that informed citizens need to know about.
Interaction Effects
Certain combinations signal especially important underreported stories:
- High coverage gap + High public interest: A story that matters but isn't being covered proportionally
- High power concentration + Accountability flags: Powerful institutions potentially avoiding scrutiny
- Cover-up indicators + Any of the above: Attempts to suppress information
These combinations can add up to 20 bonus points to the base score.
Lens Score Categories
Critical (90-100)
Major accountability stories involving high-ranking officials or institutions, with clear public interest and limited coverage. These are the stories that could change public discourse if more people knew about them.
High (70-89)
Significant underreported stories: policy decisions affecting large populations, institutional failures, or emerging issues not yet on mainstream radar.
Medium (40-69)
Stories with moderate public interest and moderate coverage. Important for those following specific topics but not urgently underreported.
Low (0-39)
Stories receiving adequate coverage relative to their importance, or content with limited public interest (entertainment, routine updates, opinion pieces).
How to Use Lens Score
In the App
- Lens Feed: Curated feed of high Lens Score stories (70+)
- Story Cards: Each story displays its Lens Score badge
- Filters: Set minimum Lens Score thresholds for your feed
For Informed News Consumption
- Start with high Lens Score stories: These are the underreported stories that matter
- Compare with trending news: Notice what's viral vs. what's important
- Follow the accountability trail: High Lens Score stories often connect to broader issues
- Share underreported stories: Help important news reach more people
What Lens Score Is NOT
It's not a virality predictor. We specifically ignore social shares and engagement metrics. Viral content often has low Lens Score because it's already getting disproportionate attention.
It's not an "importance" ranking based on coverage. Traditional importance metrics favor stories that are already widely covered. Lens Score does the opposite—it finds important stories that aren't getting coverage.
It's not editorial judgment. Lens Score is calculated algorithmically based on content analysis, not human opinions about which stories "should" matter.
Privacy
Lens Score is calculated purely on news content. It doesn't use your personal data, reading history, or preferences. The Lens Score you see is the same score everyone sees for that story.
Why This Matters
In a healthy democracy, citizens need access to information about power, accountability, and public interest—not just entertainment and outrage. But market incentives push media toward what gets clicks, not what matters.
Lens Score is our attempt to rebalance this equation. By surfacing underreported stories with genuine public interest, we help you stay informed about what powerful institutions might prefer you didn't notice.
See Lens Score in action. Download The Balanced News app free for iOS and Android.
Related Reading:
- How We Calculate Political Bias - Understanding our bias detection methodology
- How to Identify Media Bias - Learn to spot political slants in news coverage
- Political Bias in Indian Media 2025 - Where major outlets fall on the spectrum
