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Table 1 Summary of the testing and training accuracy of our allegiance determination model. For each party/coalition, we show the total number of tweets, total number of messages of the training set, as well as the number of them that have a negative (n) or a positive (p) connotation. We also provide the \(F_{1}\) and ROC AUC score

From: Design and analysis of tweet-based election models for the 2021 Mexican legislative election

Party

# of tweets

# of messages

\(F_{1}\) score

AUC

n

p

n

p

MORENA + PT

10,357,147

405

405

0.61

0.69

0.79

PVEM

239,126

65

65

0.82

0.67

0.85

PAN

1,474,845

200

200

0.47

0.68

0.61

PRI

1,248,188

235

235

0.84

0.82

0.91

PRD

1,374,029

302

302

0.82

0.79

0.85

MC

418,066

231

231

0.72

0.72

0.84

PES + FxM + RSP

262,472

285

285

0.57

0.52

0.66