get_mds_article_fits: Multidimensional scaling for article similarity

In CrumpLab/RsemanticLibrarian: Helper Functions for the Semantic Librarian

Description

Multidimensional scaling for article similarity

Usage

get_mds_article_fits(num_articles, num_clusters, year_range, input_df,
  a_vectors = article_vectors)

Arguments

num_articles	integer, number of articles to select from entire dataframe
num_clusters	integer, number of clusters to generate
year_range	vector, c(1947,1948) containing beginning to end year
input_df	dataframe an articles dataframe containing article info and Similarity info (e.g., like the one generated by get_search_article_similarities())
a_vectors	matrix, containing the article vectors (e.g., article_vectors)

Details

columns are:

• formatted_column for printing abstract info HTML

• title abstract title

• wrap_title useful for plotly hover labels

• year abstract year

• index abstract index

• Similarity of search term to abstract

• X x coordinate from MDS

• Y y coodinate from MDS

• cluster from k-means clustering

Value

dataframe, a modified version of input_df containing MDS coordinates and cluster information useful for plotting

Examples

search <- c("president")
article_dataframe<-get_search_article_similarities(search,query_type=1)
MDS <- get_mds_article_fits(10,2,c(1947,1948),article_dataframe)

CrumpLab/RsemanticLibrarian documentation built on Nov. 11, 2019, 1:04 p.m.