stylistic_similarity

This function calculates various stylistic features and their similarity
between two conversations.

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 

stylistic_similarity function

<dl><dt>text1</dt>
<dd>A character string representing the first conversation</dd>
<dt>text2</dt>
<dd>A character string representing the second conversation</dd></dl>

Arguments

Calculate stylistic similarity between two conversations — stylistic_similarity

<dl>

<dt>text1</dt>
<dd>A character string representing the first conversation</dd>


<dt>text2</dt>
<dd>A character string representing the second conversation</dd>

</dl>

stylistic_similarity: Calculate stylistic similarity between two conversations

Description

Usage

Value

Arguments

Examples