Satyameter Evidence-linked accuracy tracking for Indian TV news

← Leaderboard

Chitra Tripathi

ABP News Janhit Hindi
79.5% claim accuracy
How accuracy is measuredAccuracy = accurate ÷ (accurate + inaccurate + misleading), over verdicts with confidence ≥ 0.7. Unverifiable claims are excluded from the denominator.
0 100 79.5%

95% confidence interval 69–87%

Why we rank by the confidence boundWe rank by the lower bound of this interval, not raw accuracy. A small sample yields a wide interval and a low bound — so anchors earn their rank by being checked more, not by looking good on a handful of claims.
. 78 checked of 433 checkable · 524 extracted.

Scrutiny
What scrutiny meansN checked of M checkable — the share of this anchor's checkable claims that have actually been fact-checked. High accuracy over low scrutiny is a provisional reading, not a verdict on the anchor.
 78/433

Verdict mix

124 of 524 extracted claims checked

124 of 524 extracted claims checked.

Coverage profile

Share of extracted claims by topic — click to drill in
crime 41% communal religion 24% international 10% governance economy 6% pakistan security 6% education 5% environment 2% opposition attack 2% agriculture rural 1% other 1% science tech 1% infrastructure transport 0%

Who is held responsible
How framing is measuredThe framing target of each claim — the party the anchor assigns responsibility to. Blaming the people involved frames differently from blaming the system that enabled the issue. Counted, not judged. Click a bar to read those claims.

Framing of blame across all extracted claims · click a bar to read them
This anchor most often points at Individuals 199 claims →
Individuals 199 System & institutions 88 Government 12 Opposition 12 A minority community 2 Foreign actor 61

Flagged claims

Judged inaccurate or misleading in the checked sample

Episodes analysed

37 broadcasts

All claims & verdicts

524 claims
Claims from this anchor, newest first.
ClaimTopicVerdictConf.
The arrest papers contain confessional statements in which every arrested accused has admitted their guilt in the Ram Mandir donation theft. accused confessions crime not checked —
Only ₹1 lakh was recovered from accused number seven, Ramshankar Yadav alias Tinnu, and police suspect he may have moved additional money elsewhere. hidden stolen money crime not checked —
₹18,763 was recovered from accused number six, Karunesh Pandey. stolen money recovery crime not checked —
₹7,32,170 was recovered from accused Ramashankar Mishra. stolen money recovery crime not checked —
₹1,25,000 of stolen donation money was recovered from arrested accused Lavkush Mishra. stolen money recovery crime not checked —
Accused Anukalp Mishra also admitted committing theft and embezzlement during money counting at the temple trust, and ₹16,08,240 was recovered based on his disclosure. counting-room embezzlement crime not checked —
From accused Avinash Shukla, police recovered ₹39,220 in cash, 10,121 US dollars (over ₹1 lakh), 160 grams of silver-like metal, an approximately 8-gram gold-like chain, and an approximately 3.5-gram yellow-metal ring. cash jewellery recovery crime not checked —
Accused Avinash stated that after the theft was caught, he returned the remaining stolen donation money to the Trust, following which police seized the stolen money and jewellery from the Trust based on his disclosure. stolen money return crime not checked —
Accused Avinash Shukla admitted that theft and embezzlement took place during the counting of donation money at the temple trust. counting-room embezzlement crime not checked —
The papers shown are the arrest documents of seven of the eight accused arrested in the donation theft case. accused arrests crime not checked —
The documents are proof that the Ram Mandir Trust had complete knowledge of the donation theft. Trust cover-up crime not checked —
The documents in the anchor's possession are the confession statements of the accused in the donation theft and constitute the first firm evidence proving the theft. accused confessions crime not checked —
Champat Rai told his close aides that he will not leave Ayodhya carrying this stigma. Champat Rai response crime not checked —
ABP News was the first to make revelations holding Champat Rai responsible in the Ram Mandir donation theft case. donation theft expose crime not checked —
One should fear one's own wrongdoings rather than God; God forgives, but bad deeds never stop following you. karma morality other not checked —
According to sources, the facility may now start tomorrow, i.e., July 2. launch date governance economy not checked —
This facility for PF account holders was originally supposed to start on July 1, i.e., today. launch delay governance economy not checked —
The UPI-based PF withdrawal facility will start within the next 7 to 10 days. UPI rollout timeline governance economy not checked —
To use this facility, subscribers can go to the EPFO portal and link UPI with their bank account, and the money will come directly through their UPI. UPI linking process governance economy not checked —
For the first time, PF subscribers will get the option to withdraw PF money via UPI. UPI PF withdrawal governance economy not checked —
The entire PF withdrawal system has now been brought onto a single digital platform, which will allow money to be withdrawn quickly and easily. digital PF platform governance economy accurate 70.0%
Previously, after stating a reason, files moved between different offices for verification, forcing employees to wait a long time to withdraw their own money. PF processing delays governance economy accurate 70.0%
After the new system is implemented, subscribers can withdraw up to 75% of their PF without giving any reason. PF withdrawal limit governance economy accurate 85.0%
Until now, in many cases employees had to state a reason in order to withdraw their PF money. PF withdrawal rules governance economy accurate 90.0%
The government is very soon going to launch EPFO 2.0, after which withdrawing money from PF accounts will become extremely quick and easy. EPFO 2.0 launch governance economy inaccurate 60.0%