plot_sim_time

This function creates a ggplot object showing the similarity over time for multiple dyads.

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_sim_time function

<dl><dt>similarities</dt>
<dd>A list of similarity sequences for each dyad</dd>
<dt>title</dt>
<dd>A string specifying the plot title</dd>
<dt>y_label</dt>
<dd>A string specifying the y-axis label</dd></dl>

Arguments

Plot similarity over time for multiple dyads — plot_sim_time

<dl>

<dt>similarities</dt>
<dd>A list of similarity sequences for each dyad</dd>


<dt>title</dt>
<dd>A string specifying the plot title</dd>


<dt>y_label</dt>
<dd>A string specifying the y-axis label</dd>

</dl>

plot_sim_time: Plot similarity over time for multiple dyads

Description

Usage

Value

Arguments

Examples