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fastrg vs quanteda.textmodels

A side-by-side editorial comparison of fastrg and quanteda.textmodels — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

fastrg vs quanteda.textmodels: at a glance

Featurefastrgquanteda.textmodels
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesrandom-graphs, stochastic-blockmodels, network-sampling, sparse-matricesr-package, text-classification, nlp, quanteda
Last editorial update1h ago54m ago
WebsiteVisit →Visit →

What is fastrg?

A fast random-graph sampler that spent 0.3.1 fixing what its parameters actually mean.

fastRG samples from generalized random dot product graphs — stochastic blockmodels, degree-corrected and overlapping variants, directed and undirected — in time proportional to the number of edges rather than nodes squared, which is what makes large sparse networks tractable. Since 0.3.1 the model is constructed and parameterised in one object, with sampling methods taking that object rather than re-specifying edge distribution at sample time.

Read the full fastrg trajectory →

What is quanteda.textmodels?

Split out of quanteda, then quiet - one new classifier since 2020.

quanteda.textmodels holds the scaling and classification models factored out of quanteda's main package. The visible history is thin: a logistic regression classifier and a native C++ rewrite of svmlin in late 2020, an SVM default change in early 2021, and after that only compatibility work. The most recent release fixes a namespace break caused by quanteda 4.1.0 dropping RcppArmadillo.

Read the full quanteda.textmodels trajectory →

fastrg vs quanteda.textmodels: editorial side-by-side

F
fastrg
ANALYTICS
0.0

A fast random-graph sampler that spent 0.3.1 fixing what its parameters actually mean.

◆ Current state

fastRG samples from generalized random dot product graphs — stochastic blockmodels, degree-corrected and overlapping variants, directed and undirected — in time proportional to the number of edges rather than nodes squared, which is what makes large sparse networks tractable. Since 0.3.1 the model is constructed and parameterised in one object, with sampling methods taking that object rather than re-specifying edge distribution at sample time.

◆ Where it's heading

The package's development has been about semantic correctness more than speed. The 0.3.1 release moved edge-distribution arguments to the constructors and reinterpreted the mixing matrix S under Bernoulli parameterisation; 0.3.2 then flipped the meaning of X and Y in directed blockmodels so outgoing and incoming factors match the edge convention, and made block sorting conditional rather than unconditional. Both are corrections to what returned values mean, not to how fast they arrive. The 2025 release is CRAN documentation linking only.

◆ Prediction

With parameterisation settled and only a documentation release since 2023, the package reads as feature-complete for its sampling families. Nothing in the entries points to additional model types being queued.

Q0.0

Split out of quanteda, then quiet - one new classifier since 2020.

◆ Current state

quanteda.textmodels holds the scaling and classification models factored out of quanteda's main package. The visible history is thin: a logistic regression classifier and a native C++ rewrite of svmlin in late 2020, an SVM default change in early 2021, and after that only compatibility work. The most recent release fixes a namespace break caused by quanteda 4.1.0 dropping RcppArmadillo.

◆ Where it's heading

The package now moves when its parent or a dependency moves, not on its own schedule. Four of the six most recent releases exist to track changes in quanteda, Matrix, or CRAN policy. The modelling decisions that were made - defaulting textmodel_svm() to the L2-regularized L2-loss dual solver, reducing svmlin to a single algorithm - have not been revisited since.

◆ Prediction

The next release most likely follows another upstream change in quanteda or a Matrix and Rcpp dependency rather than adding a model.

Alternatives to fastrg and quanteda.textmodels

Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either fastrg or quanteda.textmodels.

See all fastrg alternatives → · See all quanteda.textmodels alternatives →

Recent activity from fastrg and quanteda.textmodels

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1y agofastrgDocumentation cross-linking fixes for CRAN
  2. 1y agoquanteda.textmodelsNamespace fixed after quanteda dropped RcppArmadillo
  3. 2y agofastrgDirected blockmodel X and Y factors swapped to match edge direction
  4. 3y agoquanteda.textmodelsCRAN issues and documentation fixed
  5. 3y agoquanteda.textmodelsCompatibility with Matrix 1.4.2
  6. 4y agofastrgfastRG 0.3.1
  7. 5y agoquanteda.textmodelsDuplicate example dfm removed
  8. 5y agoquanteda.textmodelsSVM default switched to the L2-regularized dual solver
  9. 5y agoquanteda.textmodelsLogistic regression classifier added; svmlin rewritten in C++

Frequently asked questions

What is the difference between fastrg and quanteda.textmodels?

Both compete on the same themes — r-package — within Analytics. fastrg and quanteda.textmodels are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is fastrg better than quanteda.textmodels?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. fastrg and quanteda.textmodels are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to fastrg?

Top fastrg alternatives in Analytics are ranked by recent ship velocity. Browse the "fastrg alternatives" section above for the current picks, or visit /alternatives/fastrg for the full list with editorial commentary on each.

What are the best alternatives to quanteda.textmodels?

Top quanteda.textmodels alternatives in Analytics are ranked by recent ship velocity. Browse the "quanteda.textmodels alternatives" section above for the current picks, or visit /alternatives/quanteda-textmodels for the full list with editorial commentary on each.