THE HEALTHY TWEET

Tweets on Infectious Diseases

@kenniajin

See what we Tweet on Helath!!!

  • The health Tweet!! shows what people tweeted between April 2013 and April 2014.
  • The focus is on the key infectious diseases that affect Sub saharan Africa.
  • The app also focuses on the following diseases.
  1. Malaria
  2. HIV
  3. Pneumonia

Example of the output

  • If you visit the App some of the things you will see are
    • Word clouds for famous words
    • Bar graphs for researchers words of interest
library("wordcloud");library(shiny) ;library(ggplot2) #make graphs in R
malariaData <- read.csv("data/Tweets_Malaria.csv")
tweetmalaria <- malariaData$content
tweetmalaria <- gsub("(f|ht)tp(s?)://(.*)[.][a-z]+", "", tweetmalaria)
tweetmalaria <- gsub("#malaria|\\# |malaria|#[mM][aA][lL][aA][rR][iI][aA]|[mM][aA][lL][aA][rR][iI][aA]|via|http", "", tweetmalaria)
tweetmalaria <- gsub("â€","", tweetmalaria)
tweetmalaria <- gsub("malaria","", tweetmalaria)
tweetmalaria <- toString(tweetmalaria)

Why Visit the Health Tweet!!

  • The three diseases of interest cause higher mortality in under fives. -Social media especially Twitter has been used as a platform for expression by differnt people in the world.

  • This app helps researchers know the perception of people on the infectious diseases and their own perceprtion.

  • It compares the key words of researc interest and what people say -i.e for malaria we focused on funding, nets, vaccines, mosquito and end

    • But the most used word on Malaria tweets was Africa and nets ---->

  • Visit the app Here for more

Where is the healthy Tweet!!

  • Here is the app visit and see
  • This word cloud shows the words used on malaria related tweets. -The famous words were Africa and Nets plot of chunk unnamed-chunk-2

Tools Used for Health Tweet

  • The app pulls sources the data from the Tweet Mapping Repo -Hosted on shinyapps.io -Uses
    1. Word cloud
    2. ggplot2
    3. Shiny the engine

Click Here to tweet a healthy one