Package index

Corpus Preparation

from_json_to_df()

Convert JSON to data.table

define_corpus()

Generate a Quanteda Corpus from a Data Table

tokenize_corpus()

Fast Corpus Tokenization

singularize_tokens()

Fast Tokens Singularization

reshape_corpus()

Fast Corpus Reshape

lookup_tokens()

Fast Tokens Lookup

Document-Level Analysis

summarize_corpus()

Fast Corpus Summarization

calculate_readability()

Fast Calculation of Readability Measures

calculate_similarity() calculate_distance()

Fast Calculation of Similarity and Distance Measures

parse_corpus()

Fast Corpus Parsing via spaCy

Built-In Dictionaries

data_dictionary_BozanicRoulstoneVanBuskirk_FLS

Bozanic Roulstone VanBuskirk Forward Looking Statement Dictionary

data_dictionary_Cannon_Ling_Wang_Watanabe

Cannon, Ling, Wang, and Watanabe CSR Dictionary

data_dictionary_Li_FLS

Feng Li Forward Looking Statement Dictionary

data_dictionary_LoughranMcDonald_Complexity

Loughran and McDonald Firm Complexity Dictionary

data_dictionary_SDG

U.N. Sustainable Development Goals (SDG) Mapping Dictionary

Topic Model API

fit_topic_model()

Fit a Topic Model Via a Unified API

as_nlp_topic_fit()

Convert Existing Topic-Model Objects to nlp_topic_fit

get_dtw()

Extract Standardized Document Topic Weights

get_tww()

Extract Standardized Topic Word Weights

get_top_terms()

Extract Top Terms from Standardized TWW

predict_topic_model()

Predict Document Topic Weights for New Data

evaluate_topic_model()

Evaluate a Fitted Topic Model

select_k_topics()

Select the Number of Topics by Grid Search

summarize_k_selection()

Summarize Topic-Count Selection Results

assess_topic_stability()

Assess Topic Stability Across Repeated Fits

summarize_topics()

Summarize Topics for Interpretation

get_representative_candidates()

Extract Representative Topic Candidates

Topic Model Plots and Backends

plot_top_terms()

Visualize Topic-Word Probabilities

plot_dtw()

Plot the Distribution of Document Topic Weights

get_stm_topic_labels()

Extract STM Topic Labels

summarize_stm_topics()

Summarize STM Topics

estimate_stm_topic_effects()

Estimate STM Topic Effects

get_topic_hyperparameters()

Extract Topic-Model Hyperparameters

get_topic_embeddings()

Extract ETM Topic Embeddings

get_term_embeddings()

Extract ETM Term Embeddings

plot_topic_embeddings()

Plot ETM Topic Embeddings

OpTop Interoperability

as_optop_weighted_dfm()

Prepare Weighted DFM Input for OpTop

as_optop_input()

Prepare NLPstudio Topic Models for OpTop

S3 Methods

plot(<nlp_k_selection>)

Plot Topic-Count Selection Results

print(<nlp_k_selection>)

Print a Compact Summary of Topic-Count Selection Results

print(<nlp_k_selection_summary>)

Print K-selection summary

print(<nlp_optop_input>)

Print OpTop input summary

print(<nlp_topic_fit>)

Print a Compact Summary of a Topic-Model Fit

print(<nlp_topic_stability>)

Print Topic Stability Results