Package: conversim 0.1.0

conversim: Conversation Similarity Analysis Package

A comprehensive toolkit for analyzing and comparing conversations. This package provides functions to calculate various similarity measures between conversations, including topic, lexical, semantic, structural, stylistic, sentiment, participant, and timing similarities. It supports both pairwise conversation comparisons and analysis of multiple dyads.

Authors:Chao Liu [aut, cre, cph]

conversim_0.1.0.tar.gz
conversim_0.1.0.zip(r-4.7-any)conversim_0.1.0.zip(r-4.6-any)conversim_0.1.0.zip(r-4.5-any)
conversim_0.1.0.tgz(r-4.6-any)conversim_0.1.0.tgz(r-4.5-any)
conversim_0.1.0.tar.gz(r-4.7-any)conversim_0.1.0.tar.gz(r-4.6-any)
conversim_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
conversim/json (API)

# Install 'conversim' in R:
install.packages('conversim', repos = c('https://chaoliu-cl.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/chaoliu-cl/conversim/issues

Pkgdown/docs site:https://liu-chao.site

On CRAN:

Conda:

4.30 score 1 stars 10 scripts 307 downloads 45 exports 64 dependencies

Last updated from:3e6d9591c5. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK197
source / vignettesOK272
linux-releaseOK163
macos-releaseOK136
macos-oldrelOK125
windows-develOK115
windows-releaseOK151
windows-oldrelOK166
wasm-releaseOK126

Exports:agg_seqcalc_sim_corcalc_sim_seqcalc_sum_statscombine_sim_seqcombine_simscompare_sim_meascompare_stylecor_sim_seqcreate_windowsgen_sim_reportheatmap_simlex_sim_seqlexical_sim_dyadslexical_similaritynorm_simparticipant_sim_dyadsplot_cor_heatmapplot_sim_compplot_sim_cor_heatmapplot_sim_multiplot_sim_seqplot_sim_timeplot_simsplot_sum_statspreprocess_dyadspreprocess_textprint_sim_reportradar_simrun_examplesem_sim_seqsemantic_sim_dyadssemantic_similaritysent_sim_seqsentiment_sim_dyadssentiment_similaritystructural_sim_dyadsstructural_similaritystyle_sim_seqstylistic_sim_dyadsstylistic_similaritytiming_sim_dyadstopic_sim_dyadstopic_sim_seqtopic_similarity

Dependencies:BHbootclicpp11data.tabledplyrdttenglishfarvergenericsggplot2gluegtableisobandlabelinglatticelexiconlifecyclelme4lsamagrittrMASSMatrixmgsubminqamodeltoolsnlmenloptrNLPpillarpkgconfigpurrrqdapRegexR6rbibutilsRColorBrewerRcppRcppEigenRcppProgressRdpackreformulasrlangS7scalessentimentrslamSnowballCstringistringrsyuzhettextcleantextshapetibbletidyrtidyselecttmtopicmodelsutf8vctrsviridisLitewithrword2vecxml2zoo

Analyzing Similarities between Two Long Speeches
Introduction | Preprocessing Text | Topic Similarity | 1. Different Algorithms | 2. Possible Reasons for LSA's High Similarity Score | 3. Sensitivity to Input Parameters | 4. Nature of the Data | Lexical Similarity | Semantic Similarity | Structural Similarity | Stylistic Similarity | Sentiment Similarity | Conclusion
Rendered fromAnalyzing_Similarities_between_Two_Long_Speeches.Rmdusingknitr::rmarkdown

Last update: 2024-09-16
Started: 2024-09-16

Analyzing Similarities in Conversational Sequence in One Dyad
Introduction | Setup | Sample Data | Topic Similarity Sequence | Lexical Similarity Sequence | Semantic Similarity Sequence | Stylistic Similarity Sequence | Sentiment Similarity Sequence | Conclusion
Rendered fromAnalyzing_Similarities_in_Conversational_Sequence_in_One_Dyad.Rmdusingknitr::rmarkdown

Last update: 2024-09-16
Started: 2024-09-16

Analyzing Similarities in Conversational Sequences across Multiple Dyads
Introduction | Setup | Loading the Data | Preprocessing | Calculating Similarities | Topic Similarity | Lexical Similarity | Semantic Similarity | Structural Similarity | Stylistic Similarity | Sentiment Similarity | Participant Similarity | Timing Similarity | Visualization | Comparing Different Similarity Measures | Conclusion
Rendered fromAnalyzing_Similarities_in_Conversational_Sequences_across_Multiple_Dyads.Rmdusingknitr::rmarkdown

Last update: 2024-09-16
Started: 2024-09-16

Utility Functions for Further Exploration and Visualization
Introduction | Combining Similarity Measures | Visualizing Similarity Scores | Comparing Stylistic Features | Generating a Comprehensive Similarity Report | Working with Conversation Sequences | Analyzing Multiple Dyads | Conclusion
Rendered fromutilities_functions.Rmdusingknitr::rmarkdown

Last update: 2024-09-16
Started: 2024-09-16

Readme and manuals

Help Manual

Help pageTopics
Aggregate Similarity Sequenceagg_seq
Calculate correlation between similarity measurescalc_sim_cor
Calculate similarity sequencecalc_sim_seq
Calculate summary statistics for similaritiescalc_sum_stats
Combine Similarity Measurescombine_sim_seq
Utility and visualization functions for speech similarity analysiscombine_sims
Compare multiple similarity measurescompare_sim_meas
Compare stylistic featurescompare_style
Calculate Correlation Between Similarity Measures for a Single Dyadcor_sim_seq
Create windows from a conversationcreate_windows
Generate similarity reportgen_sim_report
Create Similarity Heatmapheatmap_sim
Calculate lexical similarity sequence for a single dyadlex_sim_seq
Calculate lexical similarity for multiple dyadslexical_sim_dyads
Calculate lexical similarity between two conversationslexical_similarity
Normalize Similarity Scoresnorm_sim
Calculate participant similarity for multiple dyadsparticipant_sim_dyads
Plot Correlation Heatmap for a Single Dyadplot_cor_heatmap
Plot comparison of multiple similarity measuresplot_sim_comp
Plot heatmap of similarity measure correlationsplot_sim_cor_heatmap
Plot Multiple Similarity Measuresplot_sim_multi
Plot Similarity Sequenceplot_sim_seq
Plot similarity over time for multiple dyadsplot_sim_time
Visualize similarity scoresplot_sims
Plot summary statistics for similaritiesplot_sum_stats
Preprocess multiple dyad conversationspreprocess_dyads
This file contains core similarity calculation functions such as topic similarity, lexical similarity, semantic similarity, structural similarity, stylistic similarity, sentiment similarity, participant similarity, and timing similarity.preprocess_text
Print similarity reportprint_sim_report
Create Radar Chart of Average Similaritiesradar_sim
Run package examplesrun_example
Calculate semantic similarity sequence for a single dyadsem_sim_seq
Calculate semantic similarity for multiple dyadssemantic_sim_dyads
Calculate semantic similarity between two conversationssemantic_similarity
Calculate sentiment similarity sequence for a single dyadsent_sim_seq
Calculate sentiment similarity for multiple dyadssentiment_sim_dyads
Calculate sentiment similarity between two conversationssentiment_similarity
Calculate structural similarity for multiple dyadsstructural_sim_dyads
Calculate structural similarity between two conversationsstructural_similarity
Calculate stylistic similarity sequence for a single dyadstyle_sim_seq
Calculate stylistic similarity for multiple dyadsstylistic_sim_dyads
Calculate stylistic similarity between two conversationsstylistic_similarity
Calculate timing similarity for multiple dyadstiming_sim_dyads
Calculate topic similarity for multiple dyadstopic_sim_dyads
Calculate topic similarity sequence for a single dyadtopic_sim_seq
Calculate topic similarity between two conversationstopic_similarity