Word representation has always been an important research area in the history of natural
language processing (NLP). Understanding such complex text data is imperative, given that …

This work presents and assesses the power of various volumetric, sentiment, and social
network approaches to predict crucial decisions from online social media platforms. The …

The boost in the use and development of technology, spurred by COVID-19 pandemic and
its consequences, has sped up the adoption of new technologies and digital platforms in …

Explanations—a form of post-hoc interpretability—play an instrumental role in making
systems accessible as AI continues to proliferate complex and sensitive sociotechnical …

With the increasing development of Web 2.0, such as social media and online businesses,
the need for perception of opinions, attitudes, and emotions grows rapidly. Sentiment …

Social Media are sensors in the real world that can be used to measure the pulse of
societies. However, the massive and unfiltered feed of messages posted in social media is a …

We can often detect from a person's utterances whether he or she is in favor of or against a
given target entity—one's stance toward the target. However, a person may express the …

This paper studies information diffusion in social media and the potential role of bots in
influencing public opinions. Using Twitter data on the 2016 EU Referendum (“Brexit”) and …

Sentiment analysis is the task of automatically determining from text the attitude, emotion, or
some other affectual state of the author. This chapter summarizes the diverse landscape of …

Pre-processing is the first step in text classification, and choosing right pre-processing
techniques can improve classification effectiveness. We experimentally compare 16 …