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plot_network.Rd
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plot_network.Rd
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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plot_network.R
\name{plot_network}
\alias{plot_network}
\title{Visualizing the network of consecutive replies in WhatsApp chat logs}
\usage{
plot_network(
data,
names = "all",
starttime = "1960-01-01 00:00",
endtime = as.character(as.POSIXct(Sys.time(), tz = "UTC")),
return_data = FALSE,
collapse_sessions = FALSE,
edgetype = "n",
exclude_sm = FALSE
)
}
\arguments{
\item{data}{A WhatsApp chatlog that was parsed with \code{\link[WhatsR]{parse_chat}}.}
\item{names}{A vector of author names that the visualization will be restricted to. Non-listed authors will be removed.}
\item{starttime}{Datetime that is used as the minimum boundary for exclusion. Is parsed with \code{\link[anytime]{anytime}}. Standard format is "yyyy-mm-dd hh:mm". Is interpreted as UTC to be compatible with WhatsApp timestamps.}
\item{endtime}{Datetime that is used as the maximum boundary for exclusion. Is parsed with \code{\link[anytime]{anytime}}. Standard format is "yyyy-mm-dd hh:mm". Is interpreted as UTC to be compatible with WhatsApp timestamps.}
\item{return_data}{If TRUE, returns a data frame of subsequent interactions with senders and recipients. Default is FALSE.}
\item{collapse_sessions}{Whether multiple subsequent messages by the same sender should be collapsed into one row. Default is FALSE.}
\item{edgetype}{What type of content is displayed as an edge. Must be one of "TokCount","EmojiCount","SmilieCount","LocationCount","URLCount","MediaCount" or "n".}
\item{exclude_sm}{If TRUE, excludes the WhatsApp system messages from the descriptive statistics. Default is FALSE.}
}
\value{
A network visualization of authors in WhatsApp chat logs where each subsequent message is considered a reply to the previous one.
}
\description{
Plots a network for replies between authors in chat logs. Each message is evaluated as a reply to the previous one.
}
\examples{
data <- readRDS(system.file("ParsedWhatsAppChat.rds", package = "WhatsR"))
plot_network(data)
}