title: R text mining documents from CSV file (one row per doc)
body: <p>I am trying to work with the tm package in R, and have a CSV file of customer feedback with each line being a different instance of feedback. I want to import all the content of this feedback into a corpus but I want each line to be a different document within the corpus, so that I can compare the feedback in a DocTerms Matrix. There are over 10,000 rows in my data set.</p>
  
  <p>Originally I did the following:</p>
  
  <pre><code>fdbk_corpus &lt;-Corpus(VectorSource(fdbk), readerControl = list(language="eng"), sep="\t")
  </code></pre>
  
  <p>This creates a corpus with 1 document and >10,000 rows, and I want >10,000 docs with 1 row each.</p>
  
  <p>I imagine I could just have 10,000+ separate CSV or TXT documents within a folder and create a corpus from that... but I'm thinking there is a much simpler answer than that, reading each line as a separate document.</p>