plot_cor_heatmap

Plot Correlation Heatmap for a Single Dyad

Analyze and compare conversations using various similarity measures
including topic, lexical, semantic, structural, stylistic, sentiment,
participant, and timing similarities. Supports both pairwise conversation
comparisons and analysis of multiple dyads. Methods are based on established research:
Topic modeling: Blei et al. (2003) <doi:10.1162/jmlr.2003.3.4-5.993>;
Landauer et al. (1998) <doi:10.1080/01638539809545028>;
Lexical similarity: Jaccard (1912) <doi:10.1111/j.1469-8137.1912.tb05611.x>;
Semantic similarity: Salton & Buckley (1988) <doi:10.1016/0306-4573(88)90021-0>;
Mikolov et al. (2013) <doi:10.48550/arXiv.1301.3781>;
Pennington et al. (2014) <doi:10.3115/v1/D14-1162>;
Structural and stylistic analysis: Graesser et al. (2004) <doi:10.1075/target.21131.ryu>;
Sentiment analysis: Rinker (2019) <https://github.com/trinker/sentimentr>.

Chao Liu Liu

conversim

Conversation Similarity Analysis

Chao Liu 

plot_cor_heatmap function

<dl><dt>cor_matrix</dt>
<dd>A correlation matrix for a single dyad</dd>
<dt>titles</dt>
<dd>A character vector of titles for each similarity measure</dd></dl>

Arguments

Plot Correlation Heatmap for a Single Dyad — plot_cor_heatmap

<dl>

<dt>cor_matrix</dt>
<dd>A correlation matrix for a single dyad</dd>


<dt>titles</dt>
<dd>A character vector of titles for each similarity measure</dd>

</dl>

plot_cor_heatmap: Plot Correlation Heatmap for a Single Dyad

Description

Usage

Value

Arguments

Details

Examples