Sentiment analysis as a field has come a long way since it was first introduced as a task
nearly 20 years ago. It has widespread commercial applications in various domains like …

The rapid, widespread implementation of artificial intelligence technologies in workplaces
has implications for business communication. In this article, the authors describe current …

We present skweak, a versatile, Python-based software toolkit enabling NLP developers to
apply weak supervision to a wide range of NLP tasks. Weak supervision is an emerging …

Social media platforms have become an essential venue for online deliberation where users
discuss arguments, debate, and form opinions. In this paper, we propose an unsupervised …

Targeted Sentiment Analysis (TSA) is a central task for generating insights from consumer
reviews. Such content is extremely diverse, with sites like Amazon or Yelp containing …

Abstract Argument Quality Detection is an emerging field in NLP which has seen significant
recent development. However, existing datasets in this field suffer from a lack of quality …

Sentiment analysis aims to mine polarity features in the text, which can empower intelligent
terminals to recognize opinions and further enhance interaction capabilities with customers …

Polarization is an alarming trend in modern societies with serious implications on social
cohesion and the democratic process. Typically, polarization manifests itself in the public …

As the key to sentiment analysis, sentiment composition considers the classification of a
constituent via classifications of its contained sub-constituents and rules operated on them …

Increasingly, critical decisions in public policy, governance, and business strategy rely on a
deeper understanding of the needs and opinions of constituent members (eg citizens …