NAMES · WHO THE NEWS NAMED · 10-18 TO 10-31

Delhi Police

org Law enforcement agency in Delhi, India. Wikidata

Named in 4005 articles by 59 newsrooms, in 543 stories, on 14 of the last 14 days, first on 10-18.

Rank
0.1321
by the company kept · 1 is the top name
Articles
4005
6061 mentions
Linked to
1588
names in 2+ shared articles
This week
0.46×
against last week
In Congress's circle
73%
of that hub's 30 closest names are also linked here
Bridging
0.0213
between groups · 1 is the top bridge

Most exclusively tied top 30 · ties that pass the test on the right, most exclusive first

The names that appear with Delhi Police in a large share of their own coverage: this name's own company. Exclusivity runs from 0, two names that meet no more than chance would have them, to 1, two names that only ever appear together. A name that is in everything, a president, is exclusive to no one, so the big names fall away here and the names that belong to this one stay. Only ties that pass the strength test count, so a pair seen twice is not a tie. Places are context and have no page.

NameKindExclusivityTogether
Jantar Mantarperson0.7171868
Cockroach Janta Partyorg0.6861049
CJPorg0.6531942
Gyanesh Kumarperson0.6281054
Delhigpe0.5841854
Central Delhigpe0.56180
New Delhigpe0.558839
Abhijeet Dipkeperson0.558678
Saurav Dasperson0.551766
Connaught Placeorg0.54274
CECorg0.533462
ACPorg0.509113
Special Intensive Revisionorg0.506302
Uttar Pradeshorg0.475277
Election Commissionorg0.468303
Narendra Modiperson0.454423
Scrollorg0.448104
Neha Boraperson0.439246
Aam Aadmi Partyorg0.43191
Union Homeorg0.424129
Finance Ministryorg0.41496
Indian Expressorg0.411420
Gurugramorg0.40466
Capitalgpe0.39967
SIRorg0.393195
Bharatiya Janata Partyorg0.393168
FIRorg0.392195
Centregpe0.389200
ECIorg0.382111
Nationalorg0.381184

Most strongly tied the ties chance explains least

How sure the record is that two names appear together for a reason. Strength is a standard statistical test (log-likelihood): above 10.8, chance would produce the pairing less than once in a thousand times. It grows with the number of articles, so the biggest names come first here; the list on the left is where this name's own company shows.

NameStrengthTogether
Jantar Mantar150001868
CJP136841942
Delhi113511854
Cockroach Janta Party86811049
Gyanesh Kumar76681054
New Delhi5378839
Saurav Das4899766
Abhijeet Dipke4492678
CEC3061462
Narendra Modi2273423
Connaught Place2016274
Special Intensive Revision1989302
Indian Express1972420
Election Commission1793303
Uttar Pradesh1695277

Articles per day

  • 18
  • 19
  • 20
  • 21
  • 22
  • 23
  • 24
  • 25
  • 26
  • 27
  • 28
  • 29
  • 30
  • 31

The hubs' circles share of each hub's 30 closest names that are also linked to this one

The eight most-named figures each have an inner circle: the thirty names most tied to them. This is how much of each circle this name is also tied to. A count of shared company in the coverage, nothing more.

Shared with Congress: AFP, ANI, Aadhaar, Aam Aadmi Party, Abhijeet Dipke, Amit Shah, Assembly, BJP, BNS, Bandra than Goa, Bench, Bharatiya Janata Party, Bollywood, CBI, CCTV, CEC, CJP, Cabinet, Central, Cockroach Janta Party.

As the sources put it relations a model read from the stories' sources · shown when two or more stories say it

The words are the sources' words, read out by a model; nothing here reads intent. A relation from one story alone is not shown.

  • 2 stories
    Saurav Das detained by Delhi Police CJP founder Abhijeet Dipke released after preventive detention in Delhi
  • 2 stories
    Delhi Police detained and sought extended custody of Saurav Das CJP leaders Saurav Das and Ashutosh Ranka released after seven days in custody

The year 7530 articles on 56 days, 2025-11-09 to 2026-10-31 · weekly bars · 14 months on record

Left is a year ago, right is this week. Older days come from headlines only, so their counts run lower than live days.

Named together, month by month · by surprise, among that month's articles · names with a page

2026-07 Abhijeet Dipke 2 · CJP 12
2026-06 FIR 2

Stories that name Delhi Police newest edition first · 40 shown

Names are found by a language model trained to spot them, joined to one spelling per person, and counted per article. The relations are the model's reading of the sources. Everything else is a count of who was written about together; it says nothing about why.