Sentiment analysis continues to be successfully applied to consumer reviews. In other areas, the challenges involved can prove insurmountable. A failed attempt to successfully apply sentiment analysis is reported in this negative results paper. The investigators designed a system that would have been capable of recommending software libraries based on text extracted from Stack Overflow discussions. They adopted a "state-of-the-art approach based on a recursive neural network," Stanford CoreNLP, to analyze the extracted text for sentiments. A training set involving the manual labeling of sentiments required some 90 hours of work to build. Despite this best practice effort, as the final row of table 2 indicates, overall "precision and recall in detecting positive and negative sentiments [was less than] 40 percent."
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