create_windows

This function creates a list of windows from a conversation dataframe.

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 

create_windows function

<dl><dt>conversation</dt>
<dd>A dataframe containing the conversation, with a column named 'processed_text'.</dd>
<dt>window_size</dt>
<dd>An integer specifying the size of each window.</dd></dl>

Arguments

Create windows from a conversation — create_windows

<dl>

<dt>conversation</dt>
<dd>A dataframe containing the conversation, with a column named 'processed_text'.</dd>


<dt>window_size</dt>
<dd>An integer specifying the size of each window.</dd>

</dl>

create_windows: Create windows from a conversation

Description

Usage

Value

Arguments

Examples