A systematic review on affective computing: Emotion models, databases, and recent advances
Affective computing conjoins the research topics of emotion recognition and sentiment
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …
[HTML][HTML] Sentiment analysis algorithms and applications: A survey
Sentiment Analysis (SA) is an ongoing field of research in text mining field. SA is the
computational treatment of opinions, sentiments and subjectivity of text. This survey paper …
computational treatment of opinions, sentiments and subjectivity of text. This survey paper …
Aspect-based sentiment analysis via affective knowledge enhanced graph convolutional networks
Aspect-based sentiment analysis is a fine-grained sentiment analysis task, which needs to
detection the sentiment polarity towards a given aspect. Recently, graph neural models over …
detection the sentiment polarity towards a given aspect. Recently, graph neural models over …
A survey on opinion mining and sentiment analysis: tasks, approaches and applications
With the advent of Web 2.0, people became more eager to express and share their opinions
on web regarding day-to-day activities and global issues as well. Evolution of social media …
on web regarding day-to-day activities and global issues as well. Evolution of social media …
Co-LSTM: Convolutional LSTM model for sentiment analysis in social big data
Abstract Analysis of consumer reviews posted on social media is found to be essential for
several business applications. Consumer reviews posted in social media are increasing at …
several business applications. Consumer reviews posted in social media are increasing at …
Contextual semantics for sentiment analysis of Twitter
Sentiment analysis on Twitter has attracted much attention recently due to its wide
applications in both, commercial and public sectors. In this paper we present SentiCircles, a …
applications in both, commercial and public sectors. In this paper we present SentiCircles, a …
[HTML][HTML] Transformer-based deep learning models for the sentiment analysis of social media data
ST Kokab, S Asghar, S Naz - Array, 2022 - Elsevier
Sentiment analysis (SA) is a widely used contextual mining technique for extracting useful
and subjective information from text-based data. It applies on Natural Language Processing …
and subjective information from text-based data. It applies on Natural Language Processing …
News impact on stock price return via sentiment analysis
Financial news articles are believed to have impacts on stock price return. Previous works
model news pieces in bag-of-words space, which analyzes the latent relationship between …
model news pieces in bag-of-words space, which analyzes the latent relationship between …
The longest month: analyzing COVID-19 vaccination opinions dynamics from tweets in the month following the first vaccine announcement
The coronavirus outbreak has brought unprecedented measures, which forced the
authorities to make decisions related to the instauration of lockdowns in the areas most hit …
authorities to make decisions related to the instauration of lockdowns in the areas most hit …
The hourglass of emotions
Human emotions and their modelling are increasingly understood to be a crucial aspect in
the development of intelligent systems. Over the past years, in fact, the adoption of …
the development of intelligent systems. Over the past years, in fact, the adoption of …