Originating from Facebook, LinkedIn, Twitter, Instagram, YouTube, and many other
networking sites, the social media shared by users and the associated metadata are …

With the increasing number of customer reviews on the Web, there is a growing need for
effective methods to retrieve valuable information hidden in these reviews, as sellers need to …

Convolutional neural network (CNN) has lately received great attention because of its good
performance in the field of computer vision and speech recognition. It has also been widely …

The problem of uncertainty is a challenging issue to solve in opinion mining models. Existing
models that use machine learning algorithms are unable to identify uncertainty within online …

We investigate the use of Semi-Supervised Learning (SSL) in opinion detection both in
sparse data situations and for domain adaptation. We show that co-training reaches the best …

Named entity extraction is a fundamental task for many natural language processing
applications on the web. Existing studies rely on annotated training data, which is quite …

For the last decade or so, sentiment analysis, which aims to automatically identify opinions,
polarities, or emotions from user‐generated content (eg, blogs, tweets), has attracted interest …

Sentiment analysis is the computational study of how opinions, attitudes, emotions, and
perspectives are expressed in language, and has been the important task of natural …

With the explosion of publicly accessible social data, sentiment analysis has emerged as an
important task with applications in e-commerce, politics, and social sciences. Hence, so far …

Abstract Domain transfer is a widely recognized problem for machine learning algorithms
because models built upon one data domain generally do not perform well in another data …