% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/semantic_analysis.R
\name{plot_semantic_viz}
\alias{plot_semantic_viz}
\title{Plot Semantic Analysis Visualization}
\usage{
plot_semantic_viz(
  analysis_result = NULL,
  plot_type = "similarity",
  data_labels = NULL,
  color_by = NULL,
  height = 600,
  width = 800,
  title = NULL,
  coords = NULL,
  clusters = NULL,
  hover_text = NULL,
  hover_config = NULL,
  cluster_colors = NULL
)
}
\arguments{
\item{analysis_result}{A list containing semantic analysis results from functions like
semantic_similarity_analysis(), semantic_document_clustering(), or reduce_dimensions().}

\item{plot_type}{Type of visualization: "similarity" for heatmap, "dimensionality_reduction"
for scatter plot, or "clustering" for cluster visualization (default: "similarity").}

\item{data_labels}{Optional character vector of labels for data points (default: NULL).}

\item{color_by}{Optional variable to color points by in scatter plots (default: NULL).}

\item{height}{The height of the resulting Plotly plot, in pixels (default: 600).}

\item{width}{The width of the resulting Plotly plot, in pixels (default: 800).}

\item{title}{Optional custom title for the plot (default: NULL).}

\item{coords}{Optional pre-computed coordinates for dimensionality reduction plots (default: NULL).}

\item{clusters}{Optional cluster assignments vector (default: NULL).}

\item{hover_text}{Optional custom hover text for points (default: NULL).}

\item{hover_config}{Optional hover configuration list (default: NULL).}

\item{cluster_colors}{Optional color palette for clusters (default: NULL).}
}
\value{
A ggplot2 object showing the specified visualization.
}
\description{
Creates interactive visualizations for semantic analysis results including
similarity heatmaps, dimensionality reduction plots, and clustering visualizations.
}
\examples{
\donttest{
  data(SpecialEduTech)
  texts <- SpecialEduTech$abstract[1:5]
  result <- semantic_similarity_analysis(texts)
  plot <- plot_semantic_viz(result, plot_type = "similarity")
  print(plot)
}
}
\concept{visualization}
