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Finding — Did MNM/AMMK/DMDK voters move to TVK? r = +0.21

Across 207 ACs where minor third-front parties (MNM, AMMK, DMDK) had a meaningful 2021 vote share, the correlation between their 2021 share and TVK's 2026 share is +0.21. Small in absolute terms, but meaningful in direction — and explains part of TVK's geographic concentration.

The setup

In 2021, three third-front-type parties had substantial vote shares:

Party2021 ACs contestedFounded2021 statewide share
MNM (Makkal Needhi Maiam — Kamal Haasan)1802018~2.6%
AMMK (Amma Makkal Munnettra Kazhagam — Dhinakaran)1652018 (AIADMK splinter)~2.1%
DMDK (Desiya Murpokku Dravida Kazhagam — Vijayakanth)602005 (cinema-celebrity)~0.6%

By 2026, all three had effectively collapsed:

  • MNM contested 0 ACs in 2026 (party went dormant under Kamal Haasan's Rajya Sabha exit).
  • AMMK contested 11 ACs in 2026 (down from 165).
  • DMDK contested 10 ACs in 2026 (down from 60).

The hypothesis

If TVK is a celebrity-led third-front party, voters who previously chose other celebrity third-fronts (Kamal Haasan, Vijayakanth) might be the most likely TVK adopters in 2026. Did the third-front voter pool consolidate into TVK?

Test: AC-level correlation

For each of the 207 ACs where (MNM + AMMK + DMDK) had >1% combined 2021 vote share:

  • Compute their combined 2021 share (the "third-front pool" per AC)
  • Compute TVK's 2026 share in the same AC
  • Pearson correlation

Result:

MetricValue
n ACs207
Median third-front 2021 share4.51%
Median TVK 2026 share34.12%
Pearson r+0.208

What r = +0.21 means

For Indian election data, +0.2 is a real signal but not a strong one. It says:

  • ACs where third-front voters were already disposed to celebrity/anti-establishment parties did see higher TVK vote shares in 2026.
  • The effect is small relative to the noise (random forces). Most of TVK's gains came from elsewhere too — DMK and AIADMK direct switchers.
  • But it's directionally positive and statistically meaningful — not zero.

Translation

Yes, the third-front voter pool consolidated into TVK — but it was not the dominant TVK voter source. The full TVK coalition is mostly former DMK and AIADMK voters (their net swings together account for the bulk of TVK's gain), with the third-front pool contributing the rest.

Why this matters

  • It explains part of TVK's geographic concentration. Where MNM and AMMK already had >5% in 2021, TVK 2026 had a slight upward bias.
  • It's the right place to look for "Vijay inherited Kamal Haasan + Dhinakaran voters" — a clean, structured test of the theory.
  • The correlation isn't strong enough to attribute the entire TVK wave to third-front consolidation — there's a much larger flow from DMK and AIADMK.

Where it's strongest

The third-front-to-TVK signal is strongest where third-front 2021 share was high (>5%). These ACs were typically:

  • Western Tamil Nadu — Coimbatore-Tirupur belt where DMDK had pockets.
  • Chennai metro — where MNM (Kamal's geographic strongest base) had its best 2021 showing.
  • Southern TN industrial belt — where AMMK retained ex-AIADMK rural voters.

This overlaps with TVK's strongest 2026 wins, but it's not a sufficient explanation on its own.

What this isn't

  • It's NOT direct individual-level vote tracking. We're inferring from AC-level aggregates.
  • It's NOT a causal claim — high third-front 2021 share could be a proxy for "AC with celebrity-friendly voters" rather than a direct flow.
  • It's NOT enough to explain TVK's 34% statewide share. The third-front pool was only 4-5% on average.

What the data doesn't show

  • Whether the third-front voter who switched is the same person — only individual-level survey data (CSDS Lokniti) can confirm.
  • Whether DMK voters switched to TVK more in third-front-strong ACs (also possible, would amplify the effect).
  • The reverse — whether DMK/AIADMK voters in low-third-front ACs were "naturally less likely" to switch.

These are open questions a Lokniti-style post-poll could answer.

Cross-check

All numbers from S3 parquets via pipelines/deep_dive.py. Pearson r computed in pure Python.

Built from public data — ECI, Census 2011, kracekumar/tn_elections.