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require(stringr) |
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require(RCurl) |
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require(ggplot2) |
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gsqAPI = function(key,query,gid=0){ return( read.csv( paste( sep="",'http://spreadsheets.google.com/tq?', 'tqx=out:csv','&tq=', curlEscape(query), '&key=', key, '&gid=', gid) ) ) } |
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trim <- function (x) sub('@','',x) |
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twCounts=function(df){ |
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print("Counting @'d users") |
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to.count=data.frame(table(df$to)) |
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colnames(to.count)=c('Name','toCount') |
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print('Counting senders') |
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from.count=data.frame(table(df$from_user)) |
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colnames(from.count)=c('Name','fromCount') |
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print('Counting rtof users') |
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rtof.count=data.frame(table(df$rtof)) |
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colnames(rtof.count)=c('Name','rtofCount') |
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print('Counting rtby users') |
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rtby.count=data.frame(table(df$rtby)) |
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colnames(rtby.count)=c('Name','rtbyCount') |
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print('Merging datasets') |
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tmp=merge(rtof.count,to.count) |
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tmp=merge(tmp,rtby.count) |
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tmp=merge(tmp,from.count) |
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tmp$Name=factor(tmp$Name) |
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return(tmp) |
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} |
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twViz.scatter=function(df){ |
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ggplot(na.omit(df))+geom_text(aes(x=fromCount,y=toCount,label=Name,size=rtCount,angl=45)) |
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} |
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twArchParse=function(key,gid){ |
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print('Getting data') |
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df=gsqAPI(key,'select *',gid) |
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print('Got data') |
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print('Parsing @ messages') |
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df$to=sapply(df$text,function(tweet) trim(str_extract(tweet,"^(@[[:alnum:]_]*)"))) |
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print('Parsing RT: messages') |
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#THe str_match approach is really slow - I'm using it here rather than str_extract purely as a demo |
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df$rtof=sapply(df$text,function(tweet) trim(str_match(tweet,"^RT (@[[:alnum:]_]*)")[2])) |
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print('Parsing RT: senders') |
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df$rtby=paste(df$rtof,df$from_user) |
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df$rtby=sapply(df$rtby,function(dfx) if (word(dfx,1)=='NA') NA else word(dfx,2)) |
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return(df) |
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} |
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barsorter=function (dfc){ |
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htable= table(dfc) |
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hlevels=names(htable)[order(htable)] |
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return(factor(dfc, levels = hlevels)) |
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} |
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twViz.scatter2=function(df,xax='fromCount',yax='toCount',zsz='rtofCount'){ |
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ggplot(na.omit(df))+geom_text(aes_string(x=xax,y=yax,label='Name',size=zsz,angl=45)) |
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} |
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#Example usage: |
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key='0AmbQbL4Lrd61dENiT1E4SFBTbWhzVExzTElwU0NTY3c' |
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gid=82 |
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#ukgc2012=gsqAPI(key,'select *',gid) |
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ukgc2012.data=twArchParse(key,gid) |
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ukgc2012.counts=twCounts(ukgc2012.data) |
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#plot a bar chart of RT of counts |
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ggplot() + geom_bar(aes(x=na.omit(ukgc2012.data$rtof))) + opts(axis.text.x=theme_text(angle=-90,size=6)) + xlab(NULL) |
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#sorted plot based on computed counts - "RT of" |
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ukgc2012.data$hrt=barsorter(ukgc2012.data$rtof) |
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ggplot() + geom_bar(aes(x=na.omit(ukgc2012.data$hrt))) + opts(axis.text.x=theme_text(angle=-90,size=6)) + xlab(NULL) |
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#plot a bar chart of 'to' computed counts |
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ggplot() + geom_bar(aes(x=na.omit(ukgc2012.data$to))) + opts(axis.text.x=theme_text(angle=-90,size=6)) + xlab(NULL) |
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#plot a bar chart of 'from' computed counts |
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ggplot() + geom_bar(aes(x=na.omit(ukgc2012.data$from_user))) + opts(axis.text.x=theme_text(angle=-90,size=6)) + xlab(NULL) |
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#plot an ordered bar chart of 'from' tabulated counts |
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ukgc2012.counts$Name <- reorder(ukgc2012.counts$Name, ukgc2012.counts$toCount) |
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ggplot(ukgc2012.counts) + geom_bar(stat = "identity",aes(x=Name,y=toCount)) + opts(axis.text.x=theme_text(angle=-90,size=6)) + xlab(NULL) |
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#plot a scatterplot displaying to and from counts on x and ya axes, and label size as RT count |
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twViz.scatter2(ukgc2012.counts) |
