R/uiElements_network.R
In lubrunn/DSP_App_Abgabe: What the Package Does (One Line, Title Case)
#################################### going deeeper sidbarpanel
##### sidebarpanel of network tab
network_sidebar <- sidebarPanel(width = 4,
#shinyWidgets::dropdown(
#icon = icon("align-justify"),tooltip = tooltipOptions(title = "Set filters for network anylsis"),
#circle = T,
waiter::use_waitress(color = "#616f7d"),
#waiter::use_waiter(),
#waiter::use_hostess(),
#waiter::hostess_loader("load", text_color = "white", center_page = TRUE),
#### instructions button
actionButton("net_instr", "Instructions"),
###### language selector
tags$hr(),
div(id = "tweet_net_instr", tags$h4("Tweet controls"),
shinyWidgets::radioGroupButtons("lang_net", "Select Language", choiceNames = c("English Tweets", "German Tweets"),
choiceValues = c("en", "de"),
status = "primary",
checkIcon = list(
yes = icon("ok",
lib = "glyphicon"),
no = icon("remove",
lib = "glyphicon")),
size = "s"),
# company selector
selectInput("comp_net","Choose tweets for",
company_terms,
selected = "NoFilter"),
# datepicker
shinyWidgets::airDatepickerInput("dates_net", "Select a maximum of 2 days",
range = TRUE,
value = "2018-11-30",
maxDate = date_avail, minDate = "2018-11-30",
clearButton = T, update_on = "close",
multiple = 5),
textOutput("date_checker_net"),
tags$head(tags$style("#date_checker_net{color: red;
}"
)
),
##### same but continous choices
# retweets count
sliderInput("rt_net", "Choose a minimum number of retweets", min = 0, max = 1000, value = 0,
step = 1),
# likes count
sliderInput("likes_net", "Choose a minimum number of likes", min = 0, max = 1000, value = 0,
step = 1),
# long tweets switch
shinyWidgets::materialSwitch(inputId = "long_net", label = "Long Tweets only?", value = F) %>%
shinyhelper::helper(type = "inline",
title = "",
content = c("Long Tweets are tweets that contain more
than 80 characters"),
size = "s")
),
### filter by sentiment
#shinyWidgets::setSliderColor(c("red"), c(1)),
div(id = "sentiment_net_instr", sliderInput("sentiment_net", label = h5("Choose a sentiment range"),
min = -1, max = 1, value = c(-1, 1), step = 0.01, dragRange = T)
),
# filter out emoji words
div(id = "emoji_net_instr", shinyWidgets::materialSwitch(inputId = "emo_net", label = "Remove Emoji Words?", value = F) %>%
shinyhelper::helper(type = "inline",
title = "",
content = c("During the cleaning process of the tweets we replace emojis and
emoticons with text. For exmaple a lauging emoji becomes 'laughing face'.
As many tweets contain emojis these substitution words dominate the
frequency analysis. With this button you may remove these words from
the analysis in order to focus on potentially more interesting words/bigrams."),
size = "m")
),
##### additional
######### search terms
div(id = "search_net_instr", textInput("search_term_net", "Only select tweets containing the following:"),
textInput("username_net", "Only show tweets for usernames containing the following:")
),
#### optional text in case less than 4 chars input to username
textOutput("username_checker"),
tags$head(tags$style("#username_checker{color: red;
}"
)),
####### type of plot bigram/word pairs
div(id = "net_type_instr", shinyWidgets::radioGroupButtons("word_type_net",
"Select the type of word combination you would like to analyse",
choices = c("Bigram" = "bigrams_net",
"Word Pairs" = "word_pairs_net"),
status = "primary",
checkIcon = list(
yes = icon("ok",
lib = "glyphicon"),
no = icon("remove",
lib = "glyphicon")),
size = "xs")
),
##### advanced settings toggle
div(id = "adv_settings_net_instr", shinyWidgets::materialSwitch("adv_settings_net", "Advanced Settings", value = F)),
conditionalPanel(
condition = "input.adv_settings_net == true",
######## adjusting plot
numericInput("n_net", "Minimum number of occurences of a single word in the sample",
min = 10, value = 50) %>%
shinyhelper::helper(type = "inline",
title = "",
content = c("This sets the minimum number of times a single word needs to occur within
the filtered dataset. The minimum threshold is 10 or 0.1% of the numebr of tweets.
Values below these thresholds will default to the threshold for the normal
search. For the username search the values can be set as low as 1."),
size = "s"),
### panel in case of word pairs to compute word correlations
conditionalPanel(
condition = "input.word_type_net == 'word_pairs_net'",
numericInput("corr_net", "Minimum word correlation of word pairs", value = 0.15, min = 0.15, max = 1,
step = 0.01) %>%
shinyhelper::helper(type = "inline",
title = "",
content = c("This sets the minimum correlation two words need to have.
Values below 0.15 will default to 0.15. For username search this
minimum threshold is at 0.1."),
size = "s")
),
### panel for minium number of time bigrams arise
conditionalPanel(
condition = "input.word_type_net == 'bigrams_net'",
numericInput("n_bigrams_net", "Minimum number of occurences of a Bigram in the selected sample",
min = 50, value = 50)%>%
shinyhelper::helper(type = "inline",
title = "",
content = c("This sets the minimum number of times a bigram needs to occur within
the filtered dataset. The minimum threshold is 10 or 0.1% of the numebr of tweets.
Values below these thresholds will default to the threshold for the normal
search. For the username search the values can be set as low as 1."),
size = "s"),
)
),
div(id = "buttons_net_instr", actionButton("button_net", "Render Plot"),
# shinyhelper::helper(type = "markdown",
# title = "Inline Help",
# content = "network_plot_button",
# buttonLabel = "Got it!",
# easyClose = FALSE,
# fade = TRUE,
# size = "s"),
#### removing plot
shinyjs::disabled(actionButton("reset_net", "Remove Network")),
### canceling computation
shinyjs::disabled(actionButton("cancel_net", "Cancel Rendering"))
)
)
#)
####### datatable output panel
data_table_net_main <- fluidRow(column(12,
tags$br(),
tags$h4("Tweet data for current selection"),
tags$style(HTML("
.dataTables_wrapper .dataTables_length, .dataTables_wrapper .dataTables_filter, .dataTables_wrapper .dataTables_info, .dataTables_wrapper .dataTables_processing, .dataTables_wrapper .dataTables_paginate, .dataTables_wrapper .dataTables_paginate .paginate_button.current:hover {
color: #ffffff;
}
.dataTables_wrapper .dataTables_paginate .paginate_button{box-sizing:border-box;display:inline-block;min-width:1.5em;padding:0.5em 1em;margin-left:2px;text-align:center;text-decoration:none !important;cursor:pointer;*cursor:hand;color:#ffffff !important;border:1px solid transparent;border-radius:2px}
.dataTables_length select {
color: #000000;
background-color: #ffffff
}
.dataTables_filter input {
color: #000000;
background-color: #ffffff
}
thead {
color: #ffffff;
}
tbody {
color: #000000;
}
"
)),
div(id = "data_table_instr", DT::dataTableOutput("raw_tweets_net"))
)
)
##### network plot otuput panel
network_tab_main <- tabsetPanel(id = "network_analysis",
tabPanel("Description", value = 1,
tags$br(),
htmlOutput("network_description")
),
tabPanel("Network Analysis", value = 2,
tags$br(),
tags$br(),
network_sidebar,
mainPanel(
div(id = "num_tweets_info_net_instr", textOutput("number_tweets_net")),
tags$head(tags$style("#number_tweets_net{
font-size: 20px;
font-style: bold;
color: white;
}"
)
),
tags$div(id = "placeholder", style = "height: 1000px; width: 100%;")
),
tags$br(),
tags$br(),
data_table_net_main
))
lubrunn/DSP_App_Abgabe documentation built on Dec. 21, 2021, 11:51 a.m.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
#################################### going deeeper sidbarpanel
##### sidebarpanel of network tab
network_sidebar <- sidebarPanel(width = 4,
#shinyWidgets::dropdown(
#icon = icon("align-justify"),tooltip = tooltipOptions(title = "Set filters for network anylsis"),
#circle = T,
waiter::use_waitress(color = "#616f7d"),
#waiter::use_waiter(),
#waiter::use_hostess(),
#waiter::hostess_loader("load", text_color = "white", center_page = TRUE),
#### instructions button
actionButton("net_instr", "Instructions"),
###### language selector
tags$hr(),
div(id = "tweet_net_instr", tags$h4("Tweet controls"),
shinyWidgets::radioGroupButtons("lang_net", "Select Language", choiceNames = c("English Tweets", "German Tweets"),
choiceValues = c("en", "de"),
status = "primary",
checkIcon = list(
yes = icon("ok",
lib = "glyphicon"),
no = icon("remove",
lib = "glyphicon")),
size = "s"),
# company selector
selectInput("comp_net","Choose tweets for",
company_terms,
selected = "NoFilter"),
# datepicker
shinyWidgets::airDatepickerInput("dates_net", "Select a maximum of 2 days",
range = TRUE,
value = "2018-11-30",
maxDate = date_avail, minDate = "2018-11-30",
clearButton = T, update_on = "close",
multiple = 5),
textOutput("date_checker_net"),
tags$head(tags$style("#date_checker_net{color: red;
}"
)
),
##### same but continous choices
# retweets count
sliderInput("rt_net", "Choose a minimum number of retweets", min = 0, max = 1000, value = 0,
step = 1),
# likes count
sliderInput("likes_net", "Choose a minimum number of likes", min = 0, max = 1000, value = 0,
step = 1),
# long tweets switch
shinyWidgets::materialSwitch(inputId = "long_net", label = "Long Tweets only?", value = F) %>%
shinyhelper::helper(type = "inline",
title = "",
content = c("Long Tweets are tweets that contain more
than 80 characters"),
size = "s")
),
### filter by sentiment
#shinyWidgets::setSliderColor(c("red"), c(1)),
div(id = "sentiment_net_instr", sliderInput("sentiment_net", label = h5("Choose a sentiment range"),
min = -1, max = 1, value = c(-1, 1), step = 0.01, dragRange = T)
),
# filter out emoji words
div(id = "emoji_net_instr", shinyWidgets::materialSwitch(inputId = "emo_net", label = "Remove Emoji Words?", value = F) %>%
shinyhelper::helper(type = "inline",
title = "",
content = c("During the cleaning process of the tweets we replace emojis and
emoticons with text. For exmaple a lauging emoji becomes 'laughing face'.
As many tweets contain emojis these substitution words dominate the
frequency analysis. With this button you may remove these words from
the analysis in order to focus on potentially more interesting words/bigrams."),
size = "m")
),
##### additional
######### search terms
div(id = "search_net_instr", textInput("search_term_net", "Only select tweets containing the following:"),
textInput("username_net", "Only show tweets for usernames containing the following:")
),
#### optional text in case less than 4 chars input to username
textOutput("username_checker"),
tags$head(tags$style("#username_checker{color: red;
}"
)),
####### type of plot bigram/word pairs
div(id = "net_type_instr", shinyWidgets::radioGroupButtons("word_type_net",
"Select the type of word combination you would like to analyse",
choices = c("Bigram" = "bigrams_net",
"Word Pairs" = "word_pairs_net"),
status = "primary",
checkIcon = list(
yes = icon("ok",
lib = "glyphicon"),
no = icon("remove",
lib = "glyphicon")),
size = "xs")
),
##### advanced settings toggle
div(id = "adv_settings_net_instr", shinyWidgets::materialSwitch("adv_settings_net", "Advanced Settings", value = F)),
conditionalPanel(
condition = "input.adv_settings_net == true",
######## adjusting plot
numericInput("n_net", "Minimum number of occurences of a single word in the sample",
min = 10, value = 50) %>%
shinyhelper::helper(type = "inline",
title = "",
content = c("This sets the minimum number of times a single word needs to occur within
the filtered dataset. The minimum threshold is 10 or 0.1% of the numebr of tweets.
Values below these thresholds will default to the threshold for the normal
search. For the username search the values can be set as low as 1."),
size = "s"),
### panel in case of word pairs to compute word correlations
conditionalPanel(
condition = "input.word_type_net == 'word_pairs_net'",
numericInput("corr_net", "Minimum word correlation of word pairs", value = 0.15, min = 0.15, max = 1,
step = 0.01) %>%
shinyhelper::helper(type = "inline",
title = "",
content = c("This sets the minimum correlation two words need to have.
Values below 0.15 will default to 0.15. For username search this
minimum threshold is at 0.1."),
size = "s")
),
### panel for minium number of time bigrams arise
conditionalPanel(
condition = "input.word_type_net == 'bigrams_net'",
numericInput("n_bigrams_net", "Minimum number of occurences of a Bigram in the selected sample",
min = 50, value = 50)%>%
shinyhelper::helper(type = "inline",
title = "",
content = c("This sets the minimum number of times a bigram needs to occur within
the filtered dataset. The minimum threshold is 10 or 0.1% of the numebr of tweets.
Values below these thresholds will default to the threshold for the normal
search. For the username search the values can be set as low as 1."),
size = "s"),
)
),
div(id = "buttons_net_instr", actionButton("button_net", "Render Plot"),
# shinyhelper::helper(type = "markdown",
# title = "Inline Help",
# content = "network_plot_button",
# buttonLabel = "Got it!",
# easyClose = FALSE,
# fade = TRUE,
# size = "s"),
#### removing plot
shinyjs::disabled(actionButton("reset_net", "Remove Network")),
### canceling computation
shinyjs::disabled(actionButton("cancel_net", "Cancel Rendering"))
)
)
#)
####### datatable output panel
data_table_net_main <- fluidRow(column(12,
tags$br(),
tags$h4("Tweet data for current selection"),
tags$style(HTML("
.dataTables_wrapper .dataTables_length, .dataTables_wrapper .dataTables_filter, .dataTables_wrapper .dataTables_info, .dataTables_wrapper .dataTables_processing, .dataTables_wrapper .dataTables_paginate, .dataTables_wrapper .dataTables_paginate .paginate_button.current:hover {
color: #ffffff;
}
.dataTables_wrapper .dataTables_paginate .paginate_button{box-sizing:border-box;display:inline-block;min-width:1.5em;padding:0.5em 1em;margin-left:2px;text-align:center;text-decoration:none !important;cursor:pointer;*cursor:hand;color:#ffffff !important;border:1px solid transparent;border-radius:2px}
.dataTables_length select {
color: #000000;
background-color: #ffffff
}
.dataTables_filter input {
color: #000000;
background-color: #ffffff
}
thead {
color: #ffffff;
}
tbody {
color: #000000;
}
"
)),
div(id = "data_table_instr", DT::dataTableOutput("raw_tweets_net"))
)
)
##### network plot otuput panel
network_tab_main <- tabsetPanel(id = "network_analysis",
tabPanel("Description", value = 1,
tags$br(),
htmlOutput("network_description")
),
tabPanel("Network Analysis", value = 2,
tags$br(),
tags$br(),
network_sidebar,
mainPanel(
div(id = "num_tweets_info_net_instr", textOutput("number_tweets_net")),
tags$head(tags$style("#number_tweets_net{
font-size: 20px;
font-style: bold;
color: white;
}"
)
),
tags$div(id = "placeholder", style = "height: 1000px; width: 100%;")
),
tags$br(),
tags$br(),
data_table_net_main
))
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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