compare_sim_meas

This function compares multiple similarity measures for the same set of 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 

compare_sim_meas function

<dl><dt>similarity_list</dt>
<dd>A list of lists, where each inner list contains similarities for each dyad</dd>
<dt>measure_names</dt>
<dd>A vector of names for each similarity measure</dd></dl>

Arguments

Compare multiple similarity measures — compare_sim_meas

<dl>

<dt>similarity_list</dt>
<dd>A list of lists, where each inner list contains similarities for each dyad</dd>


<dt>measure_names</dt>
<dd>A vector of names for each similarity measure</dd>

</dl>

compare_sim_meas: Compare multiple similarity measures

Description

Usage

Value

Arguments

Examples