Sentiment analysis has come long way since it was introduced as a natural language
processing task nearly 20 years ago. Sentiment analysis aims to extract the underlying …

Multimodal sentiments have become the challenge for the researchers and are equally
sophisticated for an appliance to understand. One of the studies that support MS problems is …

Sentiment analysis aims to automatically uncover the underlying attitude that we hold
towards an entity. The aggregation of these sentiment over a population represents opinion …

As an emerging task in opinion mining, End-to-End Multimodal Aspect-Based Sentiment
Analysis (MABSA) aims to extract all the aspect-sentiment pairs mentioned in a pair of …

Images can convey rich semantics and induce various emotions in viewers. Recently, with
the rapid advancement of emotional intelligence and the explosive growth of visual data …

This paper introduces a visual sentiment concept classification method based on deep
convolutional neural networks (CNNs). The visual sentiment concepts are adjective noun …

Social media sentiment analysis (also known as opinion mining) which aims to extract
people's opinions, attitudes and emotions from social networks has become a research …

Entity-level (aka target-dependent) sentiment analysis of social media posts has recently
attracted increasing attention, and its goal is to predict the sentiment orientations over …

Aspect-based multimodal sentiment analysis (ABMSA) aims to determine the sentiment
polarities of each aspect or entity mentioned in a multimodal post or review. Previous studies …

Automatic assessment of sentiment from visual content has gained considerable attention
with the increasing tendency of expressing opinions via images and videos online. This …