Is "hot pizza" Positive or Negative? Mining Target-aware Sentiment Lexicons
Jie Zhou, Yuanbin Wu, Changzhi Sun, Liang He
Sentiment Analysis, Stylistic Analysis, and Argument Mining Long paper Paper
You can open the pre-recorded video in separate windows.
Abstract:
Modelling a word's polarity in different contexts is a key task in sentiment analysis. Previous works mainly focus on domain dependencies, and assume words' sentiments are invariant within a specific domain. In this paper, we relax this assumption by binding a word's sentiment to its collocation words instead of domain labels. This finer view of sentiment contexts is particularly useful for identifying commonsense sentiments expressed in neural words such as ``big'' and ``long''. Given a target (e.g., an aspect), we propose an effective ``perturb-and-see'' method to extract sentiment words modifying it from large-scale datasets. The reliability of the obtained target-aware sentiment lexicons is extensively evaluated both manually and automatically. We also show that a simple application of the lexicon is able to achieve highly competitive performances on the unsupervised opinion relation extraction task.
NOTE: Video may display a random order of authors.
Correct author list is at the top of this page.