Sentiment analysis, also called opinion mining, is a form of information extraction from text of
growing research and commercial interest. In this paper we present our machine learning …

The growing stream of content placed on the Web provides a huge collection of textual
resources. People share their experiences on-line, ventilate their opinions (and frustrations) …

In this paper we present a Hungarian sentiment corpus manually annotated at aspect level.
Our corpus consists of Hungarian opinion texts written about different types of products. The …

Hidden Markov models (HMM) have been widely used in natural language processing
(NLP), especially in syntactic level applications, which appears naturally as short-range …

Deception is a pervasive psycholinguistic phenomenon—from lies during legal trials to
fabricated online reviews. Its identification has been studied for centuries—from the ancient …

In this chapter, we present the convergence analysis and applications of particle swarm
optimization algorithm. Although it is difficult to analyze the convergence of this algorithm …

Recently, emotions and their history have become a focus point for research in different
academic fields. Traditional sentiment analysis approaches generally try to fit relatively …

The concepts of the participative Web, mass collaboration, and collective intelligence grow
out of a set of Web methodologies and technologies which improve interaction with users in …

We present an approach to creating corpora for use in detecting deception in text, including
a discussion of the challenges peculiar to this task. Our approach is based on soliciting …

Social media platforms have provided dominant arenas for people to express their opinions
and thoughts about products, services, individuals, and public policy in the form of posts …