Artificial intelligence systems, such as Sentiment Analysis (SA) systems, typically learn from
large amounts of data that may reflect human bias. Consequently, such systems may exhibit …

Sentiment analysis (SA) systems, though widely applied in many domains, have been
demonstrated to produce biased results. Some research works have been done in …

Automatic machine learning systems can inadvertently accentuate and perpetuate
inappropriate human biases. Past work on examining inappropriate biases has largely …

Sentiment analysis is used as a proxy to measure human emotion, where the objective is to
categorize text according to some predefined notion of sentiment. Sentiment analysis …

Sentiment is fundamental to human communication. Countless marketing applications mine
opinions from social media communication, news articles, customer feedback, or corporate …

The exponential growth of social media platforms such as Twitter and Facebook has
revolutionized textual communication and textual content publication in human society …

We introduce DynaSent ('Dynamic Sentiment'), a new English-language benchmark task for
ternary (positive/negative/neutral) sentiment analysis. DynaSent combines naturally …

Sentiment analysis has become a key tool for several social media applications, including
analysis of user's opinions about products and services, support to politics during …

Sentiment analysis has various application scenarios in software engineering (SE), such as
detecting developers' emotions in commit messages and identifying their opinions on Q&A …

Sentiment analysis is crucial for studying public opinion since it can provide us with valuable
information. Existing sentiment analysis methods rely on finding the sentiment element from …