In dtburk/texanaaid: An Aide for Text Analysis

# Make barplot showing distribution of reports by region and time period

out_tab <- table(full_report_meta[ , .(geog, era)])

par(family="serif", mar=c(2, 2, 2, 2))

barplot(out_tab, beside=FALSE, col=c("navy", "dodgerblue", "red"),
        border=FALSE, legend=TRUE, args.legend=list(x=2, y=24, bty="n", cex=1.5, border=FALSE),
        main=NULL)

knitr::kable(out_tab, caption=sprintf("Number of reports by geopolitical body and time period (n=%d)", num_reports))

# Table 2
knitr::kable(era_and_geog_tab, caption="Numeric indices of most prevalent topics, by geopolitical body and time period")

\pagebreak

knitr::kable(100*all_wts, caption="Average prevalence weights of each topic across all time periods, by geopolitical body", digits=0, row.names=TRUE)

\pagebreak

knitr::kable(100*all_geogs_mtrx, caption="Average prevalence weights of all topics, all geopolitical bodies", digits=0, row.names=TRUE)

\pagebreak

for(i in seq_along(wts_by_geog)) {
    w <- wts_by_geog[[i]]
    g <- names(wts_by_geog)[i]
    print(
        knitr::kable(
            100 * w, caption = sprintf("Average prevalence weights of all topics, %s", g), digits = 0, row.names = TRUE
        )
    )
}

# knitr::kable(100*eu_wts, caption="Average prevalence weights of all topics, EU", digits=0, row.names=TRUE)

# knitr::kable(100*un_wts, caption="Average prevalence weights of all topics, UN", digits=0, row.names=TRUE)

# knitr::kable(100*us_wts, caption="Average prevalence weights of all topics, US", digits=0, row.names=TRUE)

\pagebreak

for(i in 1:n_word_tables) {
    start <- 1 + (i-1)*topics_per_table
    stop <- min(i*topics_per_table, n_topics)
    print(knitr::kable(all_top_frex[ , start:stop], row.names=TRUE, caption=sprintf("Most characteristic words for topics %d-%d", start, stop)))
    if(i < n_word_tables) cat("\n\n\\pagebreak\n\n")
}