In recent years, we have witnessed a rise in fake news, ie, provably false pieces of
information created with the intention of deception. The dissemination of this type of news …

The rapid growth of the internet has reached the fourth generation, ie, web 4.0, which
supports Sentiment Analysis (SA) in many applications such as social media, marketing, risk …

Understanding user experience (UX) becomes more important in a market-driven design
paradigm because it helps designers uncover significant factors, such as user's preference …

Digital resources such as smart applications reviews and online feedback information are
important sources to seek customers' feedback and input. This paper aims to help …

Since the COVID-19 pandemic, healthcare services, particularly remote and automated
healthcare consultations, have gained increased attention. Medical bots, which provide …

Sentiment analysis is the computational examination of end user's opinion, attitudes and
emotions towards a particular topic or product. Sentiment analysis classifies the message …

Abstract Text-to-GraphQL (Text2GraphQL) is a task that converts the user's questions into
Graph+ QL (Query Language) when a graph database is given. That is a task of semantic …

Examining public attitudes is crucial for promoting effective waste sorting (WS). However,
limited studies have utilized social media data to gauge public perspectives on WS …

In recent years, supervised machine learning (ML) methods have realized remarkable
performance gains for sentiment classification utilizing labeled data. However, labeled data …

Identification, interpretation and response to customer requirements are the key success
factors for companies, regardless of their industry. Failing to satisfy customer requirements …