Social media hold valuable, vast and unstructured information on public opinion that can be
utilized to improve products and services. The automatic analysis of such data, however …

Sentiment analysis of short texts is challenging because of the limited contextual information
they usually contain. In recent years, deep learning models such as convolutional neural …

Accurate sentiment analysis models encode the sentiment of words and their combinations
to predict the overall sentiment of a sentence. This task becomes challenging when applied …

As data grow rapidly on social media by users' contributions, specially with the recent
coronavirus pandemic, the need to acquire knowledge of their behaviors is in high demand …

Sentiment analysis (also known as opinion mining) is an active research area in natural
language processing. It aims at identifying, extracting and organizing sentiments from user …

With the increase use of microblogs and social media platforms as forms of on-line
communication, we now have a huge amount of opinionated data reflecting people's …

Sentiment analysis from unstructured natural language text has recently received
considerable attention from the research community. In the frame of biologically inspired …

Sentiment analysis (SA) is the automated process of detecting and understanding the
emotions conveyed through written text. Over the past decade, SA has gained significant …

Sentiment analysis (SA) techniques are applied to assess aspects of language that are used
to express feelings, evaluations and opinions in areas such as customer sentiment …

Analyzing and understanding the sentiments of social media documents on Twitter,
Facebook, and Instagram has become a very important task at present. Analyzing the …