Emotion Detection

AbstractWe present a multi-lingual dictionary of dirty words. We have collected about 3,200 dirty words in several languages and built a database of these. The language with the most words …...

AbstractIn this paper we describe a corpus set together from two sub-corpora. The CINEMO corpus contains acted emotional expression obtained by playing dubbing exercises. This new protocol is a way …...

AbstractEmotion processing has always been a great challenge. Given the fact that an emotion is triggered by cause events and that cause events are an integral part of emotion, this …...

In this paper we present an evaluation of new techniques for automatically detecting emo- tions in text. The study estimates categorical model and dimensional model for the recogni- tion of …...

Emotions detection in the voice of patients interacting with an animated conversational agent The French ARMEN ANR-funded project aims at building an assistive robot for elderly and disabled people We …...

We describe a set of experiments using au- tomatically labelled data to train supervised classifiers for multi-class emotion detection in Twitter messages with no manual inter- vention. By cross-validating between …...

AbstractSentiment analysis is one of the recent, highly dynamic fields in Natural Language Processing. Although much research has been performed in this area, most existing approaches are based on word-level …...

AbstractThis paper presents the development of a Chinese event-based emotion corpus. It specifically describes the corpus design, collection and annotation. The proposed annotation scheme provides a consistent way of identifying …...

The advent of social media and its prosperity enable users to share their opinions and views. Understanding users’ emotional states might provide the potential to create new business opportunities. Automatically …...

AbstractIn sources used in oral history research (such as interviews with eye witnesses), passages where the degree of personal emotional involvement is found to be high can be of particular …...

AbstractThis paper presents SPA, a web-based Speech Analytics platform that integrates several speech processing modules and that makes it possible to use them through the web. It was developed with …...

AbstractAccurate detection of emotion from natural language has applications ranging from building emotional chatbots to better understanding individuals and their lives. However, progress on emotion detection has been hampered by …...

AbstractEmotion detection has a high potential positive impact on the benefit of business, society, politics or education. Given this, the main objective of our research is to contribute to the …...

AbstractDetection and classification of emotion categories expressed by a sentence is a challenging task due to subjectivity of emotion. To date, most of the models are trained and evaluated on …...

Feeling emotion is a critical characteristic to distinguish people from machines. Among all the multi-modal resources for emotion detection, textual datasets are those containing the least additional information in addition …...

AbstractThis paper describes MuTuX, our system that is designed for task 1-5a, emotion classification analysis of tweets on SemEval2018. The system aims at exploring the potential of context information of …...

AbstractIn this paper, we describe our contribution in SemEval-2018 contest. We tackled task 1 “Affect in Tweets”, subtask E-c “Detecting Emotions (multi-label classification)”. A multilabel classification system Tw-StAR was developed …...

Human emotions are complex and nuanced. Yet, an overwhelming majority of the work in automatically detecting emotions from text has focused only on classifying text into positive, negative, and neutral …...

AbstractDetecting emotion from dialogue is a challenge that has not yet been extensively surveyed. One could consider the emotion of each dialogue turn to be independent, but in this paper, …...

AbstractIn this paper, we describe a deep-learning system for emotion detection in textual conversations that participated in SemEval-2019 Task 3 “EmoContext”. We designed a specific architecture of bidirectional LSTM which …...

AbstractRecent advancements in Internet and Mobile infrastructure have resulted in the development of faster and efficient platforms of communication. These platforms include speech, facial and text-based conversational mediums. Majority of …...

AbstractWith the system description it is shown how to use the context information while detecting the emotion in a dialogue. Some guidelines about how to handle emojis was also laid …...

AbstractA suicide note is usually written shortly before the suicide and it provides a chance to comprehend the self-destructive state of mind of the deceased. From a psychological point of …...

AbstractIn recent years emotion detection in text has become more popular due to its potential applications in fields such as psychology, marketing, political science, and artificial intelligence, among others. While …...

AbstractAccurate detection of emotions in user- generated text was shown to have several applications for e-commerce, public well-being, and disaster management. Currently, the state-of-the-art performance for emotion detection in text …...

AbstractThe rise of online communication platforms has been accompanied by some undesirable effects, such as the proliferation of aggressive and abusive behaviour online. Aiming to tackle this problem, the natural …...

AbstractDetecting emotions from texts is considerably important in an NLP task, but it has the limitation of the scarcity of manually labeled data. To overcome this limitation, many researchers have …...

AbstractWe introduce XED, a multilingual fine-grained emotion dataset. The dataset consists of human-annotated Finnish (25k) and English sentences (30k), as well as projected annotations for 30 additional languages, providing new …...

AbstractThe problem of detecting psychological stress in online posts, and more broadly, of detecting people in distress or in need of help, is a sensitive application for which the ability …...

AbstractEmotion detection from social media posts has attracted noticeable attention from natural language processing (NLP) community in recent years. The ways for obtaining gold labels for training and testing of …...

AbstractEmotion detection in dialogues is challenging as it often requires the identification of thematic topics underlying a conversation, the relevant commonsense knowledge, and the intricate transition patterns between the affective …...

AbstractIn writing, humor is mainly based on figurative language in which words and expressions change their conventional meaning to refer to something without saying it directly. This flip in the …...

AbstractEmotion detection can provide us with a window into understanding human behavior. Due to the complex dynamics of human emotions, however, constructing annotated datasets to train automated models can be …...

AbstractThe long-standing goal of Artificial Intelligence (AI) has been to create human-like conversational systems. Such systems should have the ability to develop an emotional connection with the users, consequently, emotion …...

AbstractSocial media plays an increasing role in our communication with friends and family, and in our consumption of entertainment and information. Hence, to design effective ranking functions for posts on …...

AbstractCrises such as the COVID-19 pandemic continuously threaten our world and emotionally affect billions of people worldwide in distinct ways. Understanding the triggers leading to people’s emotions is of crucial …...

AbstractAutomatic emotion analysis is a highly challenging task for Natural Language Processing, which has so far mainly relied on textual contents to determine the emotion of text. However, words are …...

AbstractSocial commonsense contains many human biases due to social and cultural influence (Sap et al., 2020; Emelin et al., 2020). We focus on identifying cultural biases in data, specifically causal …...