The increasing volume of user-generated content on the web has made sentiment analysis
an important tool for the extraction of information about the human emotional state. A current …

Aspect-level sentiment analysis (ALSA) is the process of collecting, processing, analyzing,
inferring, and synthesizing subjective sentiments of entities contained in texts at the aspect …

The field of sentiment analysis, in which sentiment is gathered, analyzed, and aggregated
from text, has seen a lot of attention in the last few years. The corresponding growth of the …

Although latent factor models (eg, matrix factorization) achieve good accuracy in rating
prediction, they suffer from several problems including cold-start, non-transparency, and …

Recent advances in deep neural models allow us to build reliable named entity recognition
(NER) systems without handcrafting features. However, such methods require large …

In aspect-based sentiment analysis, extracting aspect terms along with the opinions being
expressed from user-generated content is one of the most important subtasks. Previous …

Given a bipartite graph of users and the products that they review, or followers and
followees, how can we detect fake reviews or follows? Existing fraud detection methods …

Personalized rating prediction is an important research problem in recommender systems.
Although the latent factor model (eg, matrix factorization) achieves good accuracy in rating …

Online reviews have been extensively studied in the hospitality and tourism literature.
However, while user-provided photos embedded in online reviews accumulate in large …

Recommendation and review sites offer a wealth of information beyond ratings. For
instance, on IMDb users leave reviews, commenting on different aspects of a movie (eg …