Kindly note this is a preliminary post a sort of proof of concept with limited data and code . 

Also as seen from the Histograms of the Sentiment analysis of the Twitter data  Sentiment is much more positive in the Technology Stream than in the Business stream of study.  

## -------------------------------------------

library(igraph)

library(statnet) #statnet::update_statnet()

## Loading required package: network
#1/ Load the dataset -- Loading the Network Class Object
load("studentNetwork.RData")

#2/ Make a plot of the Network --
plot(studentNetwork,main = "Student Network")

## Network attributes:

##   vertices = 205
##   directed = FALSE
##   hyper = FALSE
##   loops = FALSE
##   multiple = FALSE
##   bipartite = FALSE
##  total edges = 203
##    missing edges = 0
##    non-missing edges = 203
##  density = 0.009708274

##   vertices = 205
##   directed = FALSE
##   hyper = FALSE
##   loops = FALSE
##   multiple = FALSE
##   bipartite = FALSE
##  total edges = 203
##    missing edges = 0
##    non-missing edges = 203
##  density = 0.009708274
##
## 4.2/ Vertex attributes: accessed using %v% operator
##
##  4.2.1/ Course_of_Study:
##    character valued attribute
##    attribute summary:
##          Business         Fine_Arts      Liberal_Arts Physical_Sciences
##               109                 4                68                 6
##        Technology
##                18
##
##  4.2.2/ Sex:
##    character valued attribute
##    attribute summary:
##   F   M
##  99 106

##  4.2.3/ StudentID:
##    integer valued attribute
##    205 values
##
##  4.2.4/ Tweets:
##    character valued attribute
##    attribute summary:
##    the 10 most common values are:___________truncated output _____
                                                                                                         ## 4.2.5/  Year:
##    numeric valued attribute
##    attribute summary:
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.
##   1.000   1.000   3.000   2.732   4.000   6.000
##
## 4.3/No edge attributes : When present Edge attributes are - accessed using %e% operator

library(parallel)
library(foreach)
#Extracting students' Tweets
std.twt=studentNetwork%v%"Tweets"

#Assigning Sentiment Scores to the Tweets
tweet.score <- foreach(i=1:205,.combine='rbind') %dopar% { # the ".combine" is used as we want "foreach" to return a Numeric Vector
  # and not a list
  # %dopar% is used for Parallel processing
  words<-unlist(strsplit(std.twt[i],split="\\|")) # This "|" splits the pipe delimited string into vectors of Single Words
  Pos.match = match(words, unlist(Pos))
  Neg.match = match(words, unlist(Neg))
  Pos.match = !is.na(Pos.match) # Removing any NA from Pos.matches
  # NA{base} - The generic function is.na indicates which elements are missing.
  Neg.match = !is.na(Neg.match)

## As seen in the Histograms above the Sentiment is much more positive amongst the students of == 4^th Year as compared to students of the 2^nd Year.

 

#Histograms of Tweet Scores for Business and Technology Students respectively
hist(tweet.score[student.CoS=="Business"], main="Sentiment - Business",
     xlab="Tweet Score",col=symbol)
hist(tweet.score[student.CoS=="Technology"], main="Sentiment - Technology",
     xlab="Tweet Score",col=symbol)

## -------------------------------------------

# Source Code Courtesy -- Jeff Leek (jtleek@gmail.com)

# source(“http://biostat.jhsph.edu/~jleek/code/twitterMap.R”)

# Main - https://github.com/JulianHill/R-Tutorials

# Also See - Seems Doesnt Work on WINDOWS - https://github.com/vdimarco/twitterMap/blob/master/twitter.R

install.packages("devtools")

devtools::install_github("geoffjentry/twitteR")

# # To be used -- install.packages("base64enc")

# devtools::install_version("httr", version="0.6.0", repos="http://cran.us.r-project.org")

library("RColorBrewer", lib.loc="~/R/win-library/3.1")

library("geosphere", lib.loc="~/R/win-library/3.1")

library("maps", lib.loc="~/R/win-library/3.1")

# Rohit Comment - Seen below packages from other Twitter Example 

library("XML", lib.loc="~/R/win-library/3.1")

library("twitteR", lib.loc="~/R/win-library/3.1")

library("Rcpp", lib.loc="~/R/win-library/3.1")

library("rjson", lib.loc="~/R/win-library/3.1")

library("xml2", lib.loc="~/R/win-library/3.1")

library("bit64", lib.loc="~/R/win-library/3.1")

library("httr", lib.loc="~/R/win-library/3.1")

library("RCurl", lib.loc="~/R/win-library/3.1")

library("Rcpp", lib.loc="~/R/win-library/3.1")

library("ROAuth", lib.loc="~/R/win-library/3.1")

library("stringr", lib.loc="~/R/win-library/3.1")

library("plyr", lib.loc="~/R/win-library/3.1")

library("digest", lib.loc="~/R/win-library/3.1")

download.file(url="http://curl.haxx.se/ca/cacert.pem", destfile="cacert.pem")

api_key <- "XcRuw#################umUG"

api_secret <- "IScXQXnz#############oGabr"

access_token <- "73090441-###############B3eI7kjBmq4Y"

access_token_secret <- "za5MLQMPAA333333333333333333333vT"

setup_twitter_oauth(api_key,api_secret,access_token,access_token_secret)

## Rohit Comment - this oauth needs to be run for every session also after some break ...time not sure 

RDT<-searchTwitter("DhankarRohit")

RDT

# 

# searchTwitter("#rstats")

# 

# # d.df=twListToDf(MLB.list) ### Rohit Comment ----  MLB.list is Doubtful 

# # ??twListToDf

# 

# zz <- searchTwitter("#rstats")

# twListToDF(zz)

# -- Jeff Leek code - twitterMap("DhankarRohit") - 

twitterMap("DhankarRohit",userLocation="Gurgaon",plotType="both")

twitterMap <- function(DhankarRohit,userLocation=NULL,fileName="twitterMap.pdf",nMax = 10,plotType=c("followers","both","following")){

  

  # Get location data

  cat("Getting data from Twitter, this may take a moment.\n")

  tmp = getUser("DhankarRohit") 

  if(is.null(userLocation)){

    userLocation = location(tmp)

    userLocation = trim(userLocation)

    if(nchar(userLocation) < 2){stop("We can not find your location from Twitter")}

  }

  

# Not sure if USER NAMe is correct in this format == "DhankarRohit"

# Or it should be == DhankarRohit , without any PUNCTUATION . 

  followers=tmp$getFollowers(n=nMax)

  followersLocation = sapply(followers,function(x){location(x)})

 # nMax number of Followers 

  following = tmp$getFriends(n=nMax)

  followingLocation = sapply(following,function(x){location(x)})

 # nMax number of Following  

 

 # Load the geographic data - these all load as Class - Promise but the moment 

 # we see - str for these it turns into a DataFrame . As seen below -- 

 

 data(world.cities)

 # str(world.cities)

 # How to find - population of Delhi ...in Data Frame pop_del<- 

 # Have commented the Cities - data for US and Canada below - this 

 # Was retained as such by J Leek. Jeff Leek (jtleek@gmail.com)

 

#  data(us.cities)

#  data(canada.cities)

 

 # Find the latitude and longitude of the user - USER being SELF 

 cat("Getting geographic (latitude/longitude) of Twitter users.\n")

 userLL <- findLatLon(userLocation)$latlon

 if(any(is.na(userLL))){stop("We can't find the latitude and longitude of your location from Twitter")}

 

 # Find the latitude and longitude of each of the followers/following

 # and calcualte the distance to the user

 

 followersLL = matrix(NA,nrow=length(followers),ncol=4)

 followingLL = matrix(NA,nrow=length(following),ncol=4)

 

 ## Rohit Comment - for loop to run from - 1 to the Length of the Followers

 # Note while checking brackets for the FUNCTIONS like a FOR LOOP 

 # the corresponding - Curly Bracket shall highlight properly when cursor placed 

 # on the right side of the Curly like so === {| 

 

 for(i in 1:length(followers)){

   if(length(followersLocation[[i]]) > 0){

     tmpLL = findLatLon(trim(followersLocation[[i]]))

     if(any(!is.na(tmpLL$latlon))){

       followersLL[i,] = c(unlist(tmpLL$latlon),distCosine(userLL,tmpLL$latlon),unlist(tmpLL$cont))

     }

   }

 }

 

 for(i in 1:length(following)){

   if(length(followingLocation[[i]]) > 0){

     tmpLL = findLatLon(trim(followingLocation[[i]]))

     if(any(!is.na(tmpLL$latlon))){

       followingLL[i,] =  c(unlist(tmpLL$latlon),distCosine(userLL,tmpLL$latlon),unlist(tmpLL$cont))

     }

   }

 }

 

 ## Rohit Comment - reordering of the followers - Not sure why ? 

 

 followingLL = followingLL[order(-followingLL[,3]),]

 followersLL = followersLL[order(-followersLL[,3]),]

 

 followingLL = followingLL[!is.na(followingLL[,1]),]

 followersLL = followersLL[!is.na(followersLL[,1]),]

 

 

 cat("Plotting results.\n")

 # Set up the colors

 cols = brewer.pal(7,"Set2")

 

 # Both followers and following - here == fileName is the same given in the first 

# line/command of the code 

 if(plotType=="both"){

   pdf(fileName,height=12,width=10)

   data(worldMapEnv)

   par(mfrow=c(2,1),mar=rep(0,4))

   map('world',col="#191919",bg="black",fill=T,mar=rep(0,4),border=0)

   

   mtext(paste("@","DhankarRohit"," Follower Map",sep=""),col="lightgrey")

   nFollowers = dim(followersLL)[1]

   for(i in 1:nFollowers){

     greatC = getGreatCircle(userLL,followersLL[i,1:2])

     lines(greatC,col=cols[followersLL[i,4]],lwd=0.8)

   }

   

   legend(-180,0,legend = c(paste("Asia",sum(followingLL[,4]==1)),paste("Africa",sum(followingLL[,4]==2)),paste("N. America",sum(followingLL[,4]==3)),paste("S. America",sum(followingLL[,4]==4)),paste("Australia/N.Z.",sum(followingLL[,4]==5)),paste("Europe",sum(followingLL[,4]==6))),text.col=cols[1:6],bg="black",cex=0.75)

   

   mtext("Created by @simplystats twitterMap",side=1,adj=1,cex=0.8,col="grey")

   dev.off()

 }

## Just followers

if(plotType=="followers"){

  pdf(fileName,height=6,width=10)

  data(worldMapEnv)

  map('world',col="#191919",bg="black",fill=T,mar=rep(0,4),border=0)

  

  mtext(paste("@",userName," Follower Map",sep=""),col="lightgrey")

  nFollowers = dim(followersLL)[1]

  for(i in 1:nFollowers){

    greatC = getGreatCircle(userLL,followersLL[i,1:2])

    lines(greatC,col=cols[followersLL[i,4]],lwd=0.8)

  }

  

  legend(-180,0,legend = c(paste("Asia",sum(followersLL[,4]==1)),paste("Africa",sum(followersLL[,4]==2)),paste("N. America",sum(followersLL[,4]==3)),paste("S. America",sum(followersLL[,4]==4)),paste("Australia/N.Z.",sum(followersLL[,4]==5)),paste("Europe",sum(followersLL[,4]==6))),text.col=cols[1:6],bg="black",cex=0.75)

  mtext("Created by @simplystats twitterMap",side=1,adj=1,cex=0.8,col="grey")

  dev.off()

  

}

# Experiment --- to see how to get a Population of a City from 

# str(world.cities)

# How to find - population of Delhi ...in Data Frame pop_del<-

#  http://stackoverflow.com/questions/15303283/how-to-do-vlookup-and-fill-down-like-in-excel-in-r 

# Complete StackOverflow Page in the same Folder 

# The read.table below makes a Data.Frame out of a Text== entry , simple text converted into Data.Frame 

houses <- read.table(text="Semi            1

Single          2

Row             3

Single          2

Apartment       4

Apartment       4

Row             3",col.names=c("HouseType","HouseTypeNo"))

External Links / Recommended Reads :- 

4/ https://github.com/binukeloth/social-network-analysis/blob/master/src/network-analysis.R