solution to iviz-workshop charlotte protest shiny app: see https://ryanwesslen.shinyapps.io/protestApp/

app-prep.R

# Project 1: Charlotte Protest
library(tidyverse); library(lubridate); library(xts); library(dygraphs); library(quanteda)

# 10% sample
protestData <- readRDS("../Protest.RData") %>%
  mutate(time = paste0(substr(postedTime, 1, 13), "00:00 EDT")) %>% # convert to hourly
  mutate(time = ymd_hms(time)) %>%
  select(time, verb, postedTime, body)

# get daily counts
counts <- protestData %>% 
  count(Date = as.Date(postedTime), Type = verb) %>%
  mutate(n = n * 100) # adjust for sampling

# dygraphs

counts <- protestData %>%
  select(time, Type = verb) %>% # keep only columns
  count(time, Type) %>% # count by terms
  mutate(n = n * 100) %>% # adjust for 1% sample
  spread(key = Type, value = n, fill = 0) # pivot to xts format
  
tweet.time <- xts(
  x = counts[,-1],
  order.by = counts$time,
  tz = "EDT"
)

# quanteda

# create dfm
stopWords <- c("rt","http","t.co","https","amp", "t.c")

myCorpus <- corpus(protestData$body)
docvars(myCorpus, "time") <- protestData$time # used to filter
docvars(myCorpus, "verb") <- protestData$verb # used to filter

dfmAll <- corpus(myCorpus) %>%
  dfm(remove_punct = TRUE,
      remove_url = TRUE,
      remove = c(stopwords("English"), stopWords))

app.R

rm(list=ls()) # need to delete due to Cloud 1GB limit

library(shiny)
source("app-prep.R")
#quanteda_options("threads" = 8) # set number of threads if larger dataset/cpu

# ui
ui <- fluidPage(
    dygraphOutput("dygraph"),
    tags$hr(), # add horizontal line
    fluidRow(
        column(sliderInput("num", "Number of words", min = 10, max = 100, value = 50, step = 5), 
               checkboxInput("retweet", "Exclude Retweets", value = FALSE),
               width = 3),
        column(plotOutput("network"), width = 9)
        )
)

# server
server <- function(input, output) {
    
    output$dygraph <- renderDygraph({
        dygraph(tweet.time,  main = "Charlotte Protest Tweet Counts (1% Sample)", group = "combine") %>%
            dyLegend(show = "onmouseover") %>%
            dyOptions(colors = RColorBrewer::brewer.pal(8, "Dark2"), includeZero = TRUE) %>%
            dyAxis("x", drawGrid = FALSE) %>%
            dyOptions(useDataTimezone = TRUE) %>%
            dyRangeSelector() %>%
            dyShading(from = "2016-09-20 21:00:00", to = "2016-09-21 03:00:00") %>%
            dyShading(from = "2016-09-21 20:00:00", to = "2016-09-22 03:00:00") 
    })

    output$network <- renderPlot({
        if (!is.null(input$dygraph_date_window)) {
            minTime <- input$dygraph_date_window[[1]]
            maxTime <- input$dygraph_date_window[[2]]
        } else {
            minTime <- min(protestData$time)
            maxTime <- max(protestData$time)
        }
        
        if (input$retweet){
            dfm <- dfmAll %>%
                dfm_subset(time >= minTime & time <= maxTime & verb == "post")
        } else {
            dfm <- dfmAll %>%
                dfm_subset(time >= minTime & time <= maxTime)
        }
        
        topFeatures <- names(topfeatures(dfm, input$num))
        
        fcm(dfm) %>%
            fcm_select(topFeatures) %>% # ensure network isn't too large
            textplot_network(min_freq = 0.1, edge_alpha = 0.8, edge_size = 1)
    })
}

# Run the application 
shinyApp(ui = ui, server = server)