Sentiment analysis is a growing field at the intersection of linguistics and computer science
that attempts to automatically determine the sentiment contained in text. Sentiment can be …

Most of the recent work in sentiment analysis is carried out on textual data. The text based
sentiment analysis mainly relies on construction of word dictionaries, using machine …

In this proposal, we study the problem of understanding human sentiments from large scale
collection of Internet images based on both image features and contextual social network …

Describes work in progress to develop a standard for interoperability among high-
performance scientific components. This research stems from the growing recognition that …

Sentiment analysis is crucial for extracting social signals from social media content. Due to
huge variation in social media, the performance of sentiment classifiers using single …

Human's understanding of image content is a multi-level and multi-stage process. For visual
sentiment analysis, this process can be specified as the gradual perception from semantic to …

Studies suggest that self-harm users found it easier to discuss self-harm-related thoughts
and behaviors using social media than in the physical world. Given the enormous and …

Feature selection has shown its effectiveness to prepare high-dimensional data for many
data mining and machine learning tasks. Traditional feature selection algorithms are mainly …

With the development of artificial intelligence and deep learning, image sentiment analysis
has become a hotspot in computer vision and attracts more attention. Most of the existing …

Huge volumes of opinion-rich data is user-generated in social media at an unprecedented
rate, easing the analysis of individual and public sentiments. Sentiment analysis has shown …