calc_sum_stats

This function calculates summary statistics for the similarities of 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 

calc_sum_stats function

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

Arguments

Calculate summary statistics for similarities — calc_sum_stats

<dl>

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

</dl>

calc_sum_stats: Calculate summary statistics for similarities

Description

Usage

Value

Arguments

Examples