filterTweetsMachineLearning: Classify needs based on machine learning
In needmining: A Simple Needmining Implementation

Description Usage Arguments Details Value Author(s) Examples

filterTweetsMachineLearning classifies a list of Tweets as needs based on the random forest machine learning algorithm

1	filterTweetsMachineLearning(dataToClassify, trainingData)

`dataToClassify`	a dataframe containing the Tweet messages to classify
`trainingData`	a dataframe containing Tweets messages with a given classification (0=not a need, 1=a need)

This function uses a machine learning algorithm (random forest) to classify needs based on their content. It needs a training data set with classified needs (indicated by 0=not a need, 1=a need). This function used code fragments from the archived R packages maxent and RTextTools. The authors are Timothy P. Jurka, Yoshimasa Tsuruoka, Loren Collingwood, Amber E. Boydstun, Emiliano Grossman, Wouter van Atteveldt

a dataframe with classified data

Dorian Proksch <dorian.proksch@hhl.de>

data(NMTrainingData)
data(NMdataToClassify)
smallNMTrainingData <- rbind(NMTrainingData[1:75,], NMTrainingData[101:175,])
smallNMdataToClassify <- rbind(NMdataToClassify[1:10,], NMdataToClassify[101:110,])
results <- filterTweetsMachineLearning(smallNMdataToClassify, smallNMTrainingData)