More than a Feeling: Accuracy and Application of Sentiment Analysis

Sentiment is fundamental to human communication. Countless marketing applications mine opinions from social media communication, news articles, customer feedback, or corporate communication. Various sentiment analysis methods are available and new ones have recently been proposed. Lexicons can relate individual words and expressions to sentiment scores. In contrast, machine learning methods are more complex to interpret, but promise higher accuracy, i.e., fewer false classifications. We propose an empirical framework and quantify these trade-offs for different types of research questions, data characteristics, and analytical resources to enable informed method decisions contingent on the application context.…

• C
  Claussen-Simon-Stiftung
• DF
  Deutsche Forschungsgemeinschaft

  Awards: 460037581, HE 6703/1-2, HE 6703/1–2