R中的Twitter分析，错误：在部署应用程序时，零长度输入不能与非零长度输入混合

刚开始使用闪亮的应用程序。我在R中构建了我的代码，一切都执行得很完美，当我运行应用程序时，它也运行得很好，但是当我部署应用程序时，我得到了零长度输入的错误和无效的时间参数，这些错误导致我的绘图图表充满了我认为正在执行的错误：

从日志中：

2016-06-30T20:41:17.225966+00:00 shinyapps[111287]: Listening on http://0.0.0.0:53352
2016-06-30T20:41:19.584567+00:00 shinyapps[111287]: [1] "Using direct authentication"
2016-06-30T20:43:40.040666+00:00 shinyapps[111287]: Warning: Error in mapply: zero-length inputs cannot be mixed with those of non-zero length
2016-06-30T20:43:40.050669+00:00 shinyapps[111287]:     12: fn
2016-06-30T20:43:40.050676+00:00 shinyapps[111287]:      7: connect$retry
2016-06-30T20:43:40.050646+00:00 shinyapps[111287]: Stack trace (innermost first):
2016-06-30T20:43:40.050671+00:00 shinyapps[111287]:     11: doTryCatch
2016-06-30T20:43:40.050650+00:00 shinyapps[111287]:     85: mapply
2016-06-30T20:43:40.050672+00:00 shinyapps[111287]:     10: tryCatchOne
2016-06-30T20:43:40.050677+00:00 shinyapps[111287]:      6: eval
2016-06-30T20:43:40.050651+00:00 shinyapps[111287]:     84: Map
2016-06-30T20:43:40.050678+00:00 shinyapps[111287]:      5: eval
2016-06-30T20:43:40.050653+00:00 shinyapps[111287]:     83: colorize
2016-06-30T20:43:40.050680+00:00 shinyapps[111287]:      4: eval
2016-06-30T20:43:40.050654+00:00 shinyapps[111287]:     82: plotly_build
2016-06-30T20:43:40.050682+00:00 shinyapps[111287]:      2: eval.parent
2016-06-30T20:43:40.050655+00:00 shinyapps[111287]:     81: as.widget
2016-06-30T20:43:40.050681+00:00 shinyapps[111287]:      3: eval
2016-06-30T20:43:40.050657+00:00 shinyapps[111287]:     80: func
2016-06-30T20:43:40.050673+00:00 shinyapps[111287]:      9: tryCatchList
2016-06-30T20:43:40.050659+00:00 shinyapps[111287]:     79: output$ta2
2016-06-30T20:43:40.050674+00:00 shinyapps[111287]:      8: tryCatch
2016-06-30T20:43:40.050684+00:00 shinyapps[111287]:      1: local
2016-06-30T20:43:40.050668+00:00 shinyapps[111287]:     13: runApp

同样，当我在R中运行它时，以及当我运行闪亮应用程序时，以下功能也可以正常工作：

对于UI，我有以下代码：

用户界面

---

我认为这可能与tm软件包有关，但我在我的应用程序闪亮日志中没有看到与tm相关的功能的任何警告或错误。想法？

对qdap函数的librar调用中有一个引号，它可能会引起某种恶作剧，修复了library调用。我在脚本中的语法是正确的，所以这是我的复制粘贴问题。

ui <- fluidPage(

  #title header
  headerPanel("Main Title"),

  sidebarPanel(
    selectInput(inputId="stock", label = ("Search Stock"),
                choices = c("Select","MSFT","JPM","KO"),
                selected = NULL),#end select input

    submitButton(text="Run")

                  ),#end sidebar panel

  mainPanel(
    tabsetPanel(id="tabs1",
                tabPanel("Tweet Collection",DT::dataTableOutput('tc')),
                tabPanel("Twitter Analysis",
                         fluidRow(
                           column(12,align="center",plotlyOutput("ta1")),
                           column(12,align="center",plotlyOutput("ta2"))
                           ))
    )#end tabset panel
  )#end main panel
)#end fluid page

server <- function(input,output){

  m1 = list(
    l = 50,
    r = 50,
    b = 30,
    t = 50,
    pad = 2
  )

  m2 = list(
    l = 50,
    r = 50,
    b = 60,
    t = 50,
    pad = 2
  )

  newdata <- reactive({

    if("MSFT" %in% input$stock){

      msft <- c("#MSFT OR Microsoft OR @Microsoft")
      tweetdata <- searchTwitter(msft,lang="en",n=1500)
      tweetdata.df <- twListToDF(tweetdata)

      test <- tweetdata.df[,1]
      myvars <- c("text")
      test <- tweetdata.df[myvars]
      newdata <- test[(!duplicated(test)),]
      newdata <- as.data.frame(newdata)
      newdata <- as.data.frame(filter(newdata, !grepl('Bid Now!', newdata$newdata)))
      newdata

    } else if("JPM" %in% input$stock){

      vector <- c("#JPM OR JPMorgan OR @jpmorgan OR J.P. Morgan")
      tweetdata <- searchTwitter(vector,lang="en",n=1500)
      tweetdata.df <- twListToDF(tweetdata)

      test <- tweetdata.df[,1]
      myvars <- c("text")
      test <- tweetdata.df[myvars]
      newdata <- test[(!duplicated(test)),]
      newdata <- as.data.frame(newdata)
      newdata <- as.data.frame(filter(newdata, !grepl('Bid Now!', newdata$newdata)))
      newdata

    } else if("KO" %in% input$stock){

      ko <- c("#KO OR Coca-Cola OR @CocaCola OR @CocaColaCo OR Coca Cola")
      tweetdata <- searchTwitter(ko,lang="en",n=1500)
      tweetdata.df <- twListToDF(tweetdata)

      test <- tweetdata.df[,1]
      myvars <- c("text")
      test <- tweetdata.df[myvars]
      newdata <- test[(!duplicated(test)),]
      newdata <- as.data.frame(newdata)
      newdata <- as.data.frame(filter(newdata, !grepl('Bid Now!', newdata$newdata)))
      newdata

    }

  })

####SOME AUTHENTICATION SET UP FOR TWITTER HERE####

#text analysis tab
  output$ta1 <- renderPlotly({

    if("Select" %in% input$stock){

      plot_ly(x=c(1,2,3,4,5), y=c(1,2,3,4,5))%>%
        layout(title="No Data Selected", margin=m1)

    } else if (!("Select" %in% input$stock)){

      # analyze the association between frequent terms (i.e., terms which correlate)
      myCorpus <- Corpus(VectorSource(newdata()[,1]))
      toSpace <- content_transformer(function (x , pattern ) gsub(pattern, " ", x))
      myCorpus <- tm_map(myCorpus, toSpace, "/")
      myCorpus <- tm_map(myCorpus, toSpace, "@")
      myCorpus <- tm_map(myCorpus, toSpace, "\\|")
      myCorpus <- tm_map(myCorpus, stripWhitespace)
      myCorpus <- tm_map(myCorpus, tolower)
      myCorpus <- tm_map(myCorpus, removeWords,c(stopwords(kind = "en"),"https","tco","coca","cola","jpm","microsoft","jpmorgan","morgan"))
      myCorpus <- tm_map(myCorpus, removePunctuation)
      myCorpus <- tm_map(myCorpus, removeNumbers)
      myCorpus <- tm_map(myCorpus, stemDocument, "english")
      myCorpus <- tm_map(myCorpus, PlainTextDocument)
      dtm <- TermDocumentMatrix(myCorpus)
      m <- as.matrix(dtm)
      v <- sort(rowSums(m),decreasing=TRUE)
      d <- data.frame(word = names(v),newfreq=v)

      plot_ly(x=d[1:10,1], y=d[1:10,2], color=as.ordered(d[1:10,2]), showlegend=F,type='bar') %>%
        layout(title="Most Frequent Words Found in Collected Tweets",margin=m2,xaxis=list(title=" "),yaxis=list(title="Frequency"))
    }

  })#end ta1 output

myCorpus <- tm_map(myCorpus, tolower, lazy=true) ...etc

myCorpus <- tm_map(myCorpus, content_transformer(tolower)) ...etc

tm_map(r_stats_text_corpus,
                              content_transformer(function(x) iconv(x, to='UTF-8', sub='byte')),
                              mc.cores=1
                              ) ...used this right underneath my corpus call

library(bitops)
library(data.table)
library(dplyr)
library(ggplot2)
library(maptpx)
library(plotly)
library(plyr)
library(qdap)
library(RColorBrewer)
library(RCurl)
library(rjson)
library(ROAuth)
library(RWeka)
library(streamR)
library(textir)
library(tm)
library(twitteR)
library(varhandle)
library(wordnet)
library(shiny)
library(devtools)
library(rsconnect)
library(SnowballC)