相关论文: Emotion Intensities in Tweets

In the field of Natural Language Processing, information extraction from texts has been the objective of many researchers for years. Many different techniques have been applied in order to reveal the opinion that a tweet might have, thus…

Sentiment analysis has various application scenarios in software engineering (SE), such as detecting developers' emotions in commit messages and identifying their opinions on Q&A forums. However, commonly used out-of-the-box sentiment…

We propose leveraging cognitive science research on emotions and communication to improve language models for emotion analysis. First, we present the main emotion theories in psychology and cognitive science. Then, we introduce the main…

In this study, we explore the application of transformer-based models for emotion classification on text data. We train and evaluate several pre-trained transformer models, on the Emotion dataset using different variants of transformers.…

In recent years, emotion detection in text has become more popular due to its vast potential applications in marketing, political science, psychology, human-computer interaction, artificial intelligence, etc. In this work, we argue that…

We introduce a novel approach to emotion modeling that shifts the focus from identification to evaluation, addressing the limitations of discrete classification in applied domains such as finance. By constructing a dataset of emotional…

Automatic sentiment analysis play vital role in decision making. Many organizations spend a lot of budget to understand their customer satisfaction by manually going over their feedback/comments or tweets. Automatic sentiment analysis can…

Sentiment analysis is a well-known natural language processing task that involves identifying the emotional tone or polarity of a given piece of text. With the growth of social media and other online platforms, sentiment analysis has become…

Sentiment Analysis is a well-studied field of Natural Language Processing. However, the rapid growth of social media and noisy content within them poses significant challenges in addressing this problem with well-established methods and…

The importance of quantifying the nature and intensity of emotional states at the level of populations is evident: we would like to know how, when, and why individuals feel as they do if we wish, for example, to better construct public…

Whenever human beings interact with each other, they exchange or express opinions, emotions, and sentiments. These opinions can be expressed in text, speech or images. Analysis of these sentiments is one of the popular research areas of…

Text is the major method that is used for communication now a days, each and every day lots of text are created. In this paper the text data is used for the classification of the emotions. Emotions are the way of expression of the persons…

Sentiment analysis of social media data is an emerging field with vast applications in various domains. In this study, we developed a sentiment analysis model to analyze social media sentiment, especially tweets, during global conflicting…

A sentiment analysis system powered by machine learning was created in this study to improve real-time social network public opinion monitoring. For sophisticated sentiment identification, the suggested approach combines cutting-edge…

Emotion detection is pivotal in human communication, as it significantly influences behavior, relationships, and decision-making processes. This study concentrates on text-based emotion detection by leveraging the GoEmotions dataset, which…

It is often difficult to correctly infer a writer's emotion from text exchanged online, and differences in recognition between writers and readers can be problematic. In this paper, we propose a new framework for detecting sentences that…

Social media channels, such as Facebook, Twitter, and Instagram, have altered our world forever. People are now increasingly connected than ever and reveal a sort of digital persona. Although social media certainly has several remarkable…

Several messages express opinions about events, products, and services, political views or even their author's emotional state and mood. Sentiment analysis has been used in several applications including analysis of the repercussions of…

Emotion detection from text seeks to identify an individual's emotional or mental state - positive, negative, or neutral - based on linguistic cues. While significant progress has been made for English and other high-resource languages,…

This study aimed to investigate the influence of the presence of informal language, such as emoticons and slang, on the performance of sentiment analysis models applied to social media text. A convolutional neural network (CNN) model was…