Sentiment Analysis (SA), also called Opinion Mining, is currently one of the most studied
research fields. It aims to analyze people's sentiments, opinions, attitudes, emotions, etc …

Emotions play an important role in the learning process. Considering the learner's emotions
is essential for electronic learning (e-learning) systems. Some researchers have proposed …

With the widespread usage of social networks, forums and blogs, customer reviews
emerged as a critical factor for the customers' purchase decisions. Since the beginning of …

Social networks have changed the communication patterns significantly. Information
available from different social networking sites can be well utilized for the analysis of users …

The new transformed read-write Web has resulted in a rapid growth of user generated
content on the Web resulting into a huge volume of unstructured data. A substantial part of …

Studying the relationship between public sentiment and stock prices has been the focus of
several studies. This paper analyzes whether the sentiment expressed in Twitter feeds …

Multi-label feature selection is regarded as one of the most promising techniques that can be
used to maximize the efficacy and efficiency of multi-label classification. However, because …

Hybrid recommender systems utilize advanced algorithms capable of learning
heterogeneous sources of data and generating personalized recommendations for users …

With the rapid proliferation of Web 2.0, the identification of emotions embedded in user-
contributed comments at the social web is both valuable and essential. By exploiting large …

Deep neural networks (DNN) have achieved remarkable results in sentiment classification.
Some ensemble methods of DNN models and traditional feature-based models are …