Publications by Group L
Group L final revised version
Overview For this project, we explored two datasets – tweets about the Covid-19 vaccine and the reported side effects of the vaccine. Firstly, we looked into what people are discussing when they tweet about the Covid-19 vaccine and explored their feelings about it. This would give us some insight into people’s general attitudes towards it. Se...
8681 sym R (4931 sym/8 pcs) 19 img
groupLcovid-19vaccine
Overview For this project, we explored two datasets – tweets about Covid-19 vaccine and the reported side effects of the vaccine. Firstly, we looked into what people are discussing when they tweet about Covid-19 vaccine. Then we narrowed it down to the side effect discussions, to see what’s commonly mentioned here and where the tweets were se...
8983 sym R (20919 sym/25 pcs) 23 img
Covid-19 Vac Side Effect
packages <- c("devtools","knitr","tidyverse","widgetframe","readr", "wordcloud", "base64enc", "tidytext", "RWeka","stats","manifestoR","readtext", "rvest", "stringr", "SnowballC", "plotrix", "tidyr", "tidytext", "stats", "dendextend", "ggthemes", "httr","jsonli...
4240 sym R (11486 sym/8 pcs) 7 img
NYC parking violation
packages <- c("devtools","knitr","tidyverse","widgetframe","readr", "leaflet","RColorBrewer","rgdal", "leaflet.extras","DT","ggmap", "ggthemes","readr","maptools","mapproj","rgeos","rgdal","RColorBrewer","stringr","scales","tidyverse","readxl","statebins","RJSONIO","XML", "xfun", "sf", "osmdata","tmap", "tmaptools","lw...
4736 sym R (16362 sym/38 pcs) 9 img
kickstarter
packages <- c("devtools","knitr","tidyverse","widgetframe","readr", "wordcloud", "base64enc", "tm", "quanteda", "qdapDictionaries", "tidytext", "RWeka","stats","manifestoR","readtext", "rvest", "stringr", "SnowballC", "plotrix", "tidyr", "tidytext", "stats", "d...
1733 sym R (13336 sym/24 pcs) 7 img
U.S. Senators on Twitter
library(tidyverse) library(igraph) library(ggraph) library(ggthemes) library(readr) 1. Who follows whom? a) Network of Followers follow <- read_csv("senators_follow.csv") senators <- read_csv("senators_twitter.csv") #filter to see who follows who fol <- follow %>% filter(following == "TRUE") %>% select(source, target) #the nodes nodes ...
2687 sym R (6398 sym/6 pcs) 5 img