On the public citation graph

Emotion Ontology Studies: A Framework for Expressing Feelings Digitally and its Application to Sentiment Analysis

0 signed · 274 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

1 of the 200 references listed on this page is in the Retraction Watch database as retracted (export 2026-11-11): 10.1007/s10586-017-1200-1 (notice 2022-12-05).

Dataset join, best-effort; this page does not check the publisher record. Retraction Watch data via Crossref Labs, used with credit; OpenCitations Index (CC0) and Meta (CC BY 4.0); dataset doi:10.7910/DVN/WT8VOA (CC BY 4.0).

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/0470013494.ch3openalex-snapshot
Basic Emotions
inferredcites →https://doi.org/10.1002/0470013494.ch30openalex-snapshot
Appraisal Theory
inferredcites →https://doi.org/10.1002/asi.21416openalex-snapshot
Sentiment strength detection in short informal text
inferredcites →https://doi.org/10.1002/asi.22768openalex-snapshot
Sentiment analysis of twitter audiences: Measuring the positive or negative influence of popular twitterers
inferredcites →https://doi.org/10.1002/cpe.6479openalex-snapshot
Rumor, misinformation among web: A contemporary review of rumor detection techniques during different web waves
inferredcites →https://doi.org/10.1002/hbe2.239openalex-snapshot
Public emotion responses during COVID ‐19 in China on social media: An observational study
inferredcites →https://doi.org/10.1002/isaf.1424openalex-snapshot
Toward an ontology‐driven blockchain design for supply‐chain provenance
inferredcites →https://doi.org/10.1006/knac.1993.1008openalex-snapshot
A translation approach to portable ontology specifications
inferredcites →https://doi.org/10.1007/11428817_21openalex-snapshot
Text2Onto
inferredcites →https://doi.org/10.1007/11573548_45openalex-snapshot
Annotation of Emotions and Feelings in Texts
inferredcites →https://doi.org/10.1007/11573548_65openalex-snapshot
An Ontology for Description of Emotional Cues
inferredcites →https://doi.org/10.1007/978-1-137-07946-6openalex-snapshot
Emotion Science
inferredcites →https://doi.org/10.1007/978-1-4614-3223-4_12openalex-snapshot
Text Analytics in Social Media
inferredcites →https://doi.org/10.1007/978-1-84628-710-7_8openalex-snapshot
Methods for Ontology Development
inferredcites →https://doi.org/10.1007/978-3-030-36599-8_5openalex-snapshot
Emotional Concept Extraction Through Ontology-Enhanced Classification
inferredcites →https://doi.org/10.1007/978-3-319-21996-7_2openalex-snapshot
An Ontology-Based Question System for a Virtual Coach Assisting in Trauma Recollection
inferredcites →https://doi.org/10.1007/978-3-540-73354-6_34openalex-snapshot
OntoGen: Semi-automatic Ontology Editor
inferredcites →https://doi.org/10.1007/978-3-540-74628-7_27openalex-snapshot
Identifying Expressions of Emotion in Text
inferredcites →https://doi.org/10.1007/978-3-540-87781-3_11openalex-snapshot
Towards an Ontology for Describing Emotions
inferredcites →https://doi.org/10.1007/978-3-642-04391-8_32openalex-snapshot
Developing HEO Human Emotions Ontology
inferredcites →https://doi.org/10.1007/978-3-642-05148-7_9openalex-snapshot
Formalized Conflicts Detection Based on the Analysis of Multiple Emails: An Approach Combining Statistics and Ontologies
inferredcites →https://doi.org/10.1007/978-3-642-11198-3_6openalex-snapshot
Architecture for Affective Social Games
inferredcites →https://doi.org/10.1007/978-3-642-19208-1_7openalex-snapshot
Methodology for Engineering Affective Social Applications
inferredcites →https://doi.org/10.1007/978-3-642-25126-9_6openalex-snapshot
FTMOntology: An Ontology to Fill the Semantic Gap between Music, Mood, Personality, and Human Physiology
inferredcites →https://doi.org/10.1007/978-3-642-25631-8_22openalex-snapshot
Emotion Tokens: Bridging the Gap among Multilingual Twitter Sentiment Analysis
inferredcites →https://doi.org/10.1007/978-3-642-34584-5_11openalex-snapshot
The Hourglass of Emotions
inferredcites →https://doi.org/10.1007/978-3-642-54903-8_9openalex-snapshot
Investigating the Role of Emotion-Based Features in Author Gender Classification of Text
inferredcites →https://doi.org/10.1007/978-3-662-49619-0_8openalex-snapshot
Semantic Web-Based Social Media Analysis
inferredcites →https://doi.org/10.1007/s00521-018-3476-3openalex-snapshot
RETRACTED ARTICLE: Classifying streaming of Twitter data based on sentiment analysis using hybridization
inferredcites →https://doi.org/10.1007/s00521-018-3825-2openalex-snapshot
Cross-domain aspect/sentiment-aware abstractive review summarization by combining topic modeling and deep reinforcement learning
inferredcites →https://doi.org/10.1007/s00521-018-3867-5openalex-snapshot
Emotional sentiment analysis for a group of people based on transfer learning with a multi-modal system
inferredcites →https://doi.org/10.1007/s10115-010-0320-1openalex-snapshot
Ontological reasoning for improving the treatment of emotions in text
inferredcites →https://doi.org/10.1007/s10462-016-9472-zopenalex-snapshot
Aspect extraction in sentiment analysis: comparative analysis and survey
inferredcites →https://doi.org/10.1007/s10462-017-9599-6openalex-snapshot
A survey on classification techniques for opinion mining and sentiment analysis
inferredcites →https://doi.org/10.1007/s10462-019-09782-9openalex-snapshot
Automatic ontology construction from text: a review from shallow to deep learning trend
inferredcites →https://doi.org/10.1007/s10462-019-09794-5openalex-snapshot
Sentiment analysis using deep learning architectures: a review
inferredcites →https://doi.org/10.1007/s10462-022-10144-1openalex-snapshot
A survey on sentiment analysis methods, applications, and challenges
inferredcites →https://doi.org/10.1007/s10462-022-10224-2openalex-snapshot
A survey on deep reinforcement learning for audio-based applications
inferredcites →https://doi.org/10.1007/s10579-018-9420-4openalex-snapshot
Building and evaluating resources for sentiment analysis in the Greek language
inferredcites →https://doi.org/10.1007/s10586-017-1200-1openalex-snapshot
RETRACTED ARTICLE: Classification of sentence level sentiment analysis using cloud machine learning techniques
inferredcites →https://doi.org/10.1007/s10660-019-09354-7openalex-snapshot
Sentiment analysis for online reviews using conditional random fields and support vector machines
inferredcites →https://doi.org/10.1007/s10865-016-9768-0openalex-snapshot
Behavior change interventions: the potential of ontologies for advancing science and practice
inferredcites →https://doi.org/10.1007/s11042-009-0332-6openalex-snapshot
Music emotion classification and context-based music recommendation
inferredcites →https://doi.org/10.1007/s11042-011-0815-0openalex-snapshot
Sentic Computing for social media marketing
inferredcites →https://doi.org/10.1007/s11042-013-1624-4openalex-snapshot
STIMONT: a core ontology for multimedia stimuli description
inferredcites →https://doi.org/10.1007/s11042-018-6168-1openalex-snapshot
Deep neural network architecture for sentiment analysis and emotion identification of Twitter messages
inferredcites →https://doi.org/10.1007/s11042-019-07813-9openalex-snapshot
An effective approach for emotion detection in multimedia text data using sequence based convolutional neural network
inferredcites →https://doi.org/10.1007/s11280-012-0181-5openalex-snapshot
Ontology-based context modeling for emotion recognition in an intelligent web
inferredcites →https://doi.org/10.1007/s12559-011-9101-8openalex-snapshot
Sentic Web: A New Paradigm for Managing Social Media Affective Information
inferredcites →https://doi.org/10.1007/s12559-012-9145-4openalex-snapshot
Sentic Album: Content-, Concept-, and Context-Based Online Personal Photo Management System
inferredcites →https://doi.org/10.1007/s12559-021-09824-xopenalex-snapshot
Ten Years of Sentic Computing
inferredcites →https://doi.org/10.1007/s12559-022-10025-3openalex-snapshot
Text Analysis of Evolving Emotions and Sentiments in COVID-19 Twitter Communication
inferredcites →https://doi.org/10.1016/0092-6566(77)90037-xopenalex-snapshot
Evidence for a three-factor theory of emotions
inferredcites →https://doi.org/10.1016/0148-2963(82)90016-9openalex-snapshot
Impulsive consumer buying as a result of emotions
inferredcites →https://doi.org/10.1016/0191-8869(91)90043-bopenalex-snapshot
Handbook of personality theory and research
inferredcites →https://doi.org/10.1016/b978-0-12-558701-3.50001-6openalex-snapshot
EMOTION: Theory, Research, and Experience
inferredcites →https://doi.org/10.1016/b978-0-12-558701-3.50007-7openalex-snapshot
A GENERAL PSYCHOEVOLUTIONARY THEORY OF EMOTION
inferredcites →https://doi.org/10.1016/b978-0-12-558701-3.50018-1openalex-snapshot
A CONSTRUCTIVIST VIEW OF EMOTION
inferredcites →https://doi.org/10.1016/b978-0-12-558704-4.50011-6openalex-snapshot
THE DICTIONARY OF AFFECT IN LANGUAGE
inferredcites →https://doi.org/10.1016/j.asej.2014.04.011openalex-snapshot
Sentiment analysis algorithms and applications: A survey
inferredcites →https://doi.org/10.1016/j.asoc.2015.01.007openalex-snapshot
Electroencephalogram-based emotion assessment system using ontology and data mining techniques
inferredcites →https://doi.org/10.1016/j.bica.2013.01.001openalex-snapshot
The emergence of (artificial) emotions from cognitive and neurological processes
inferredcites →https://doi.org/10.1016/j.chb.2013.05.024openalex-snapshot
Sentiment analysis in Facebook and its application to e-learning
inferredcites →https://doi.org/10.1016/j.chb.2014.11.100openalex-snapshot
Emotions ontology for collaborative modelling and learning of emotional responses
inferredcites →https://doi.org/10.1016/j.chb.2018.07.006openalex-snapshot
User sentiment analysis based on social network information and its application in consumer reconstruction intention
inferredcites →https://doi.org/10.1016/j.chb.2018.08.051openalex-snapshot
Recommendations-based on semantic analysis of social networks in learning environments
inferredcites →https://doi.org/10.1016/j.csl.2013.04.010openalex-snapshot
Automatically annotating a five-billion-word corpus of Japanese blogs for sentiment and affect analysis
inferredcites →https://doi.org/10.1016/j.dss.2012.05.024openalex-snapshot
Detecting implicit expressions of emotion in text: A comparative analysis
inferredcites →https://doi.org/10.1016/j.dss.2012.05.030openalex-snapshot
From once upon a time to happily ever after: Tracking emotions in mail and books
inferredcites →https://doi.org/10.1016/j.dss.2012.11.013openalex-snapshot
Development and evaluation of ontology for intelligent decision support in medical emergency management for mass gatherings
inferredcites →https://doi.org/10.1016/j.dss.2018.09.002openalex-snapshot
Deep learning for affective computing: Text-based emotion recognition in decision support
inferredcites →https://doi.org/10.1016/j.eswa.2009.06.099openalex-snapshot
Automatic event-level textual emotion sensing using mutual action histogram between entities
inferredcites →https://doi.org/10.1016/j.eswa.2012.07.025openalex-snapshot
Affect analysis in context of characters in narratives
inferredcites →https://doi.org/10.1016/j.eswa.2013.01.001openalex-snapshot
Ontology-based sentiment analysis of twitter posts
inferredcites →https://doi.org/10.1016/j.eswa.2013.05.057openalex-snapshot
Twitter brand sentiment analysis: A hybrid system using n-gram analysis and dynamic artificial neural network
inferredcites →https://doi.org/10.1016/j.eswa.2014.03.022openalex-snapshot
Feature-based opinion mining through ontologies
inferredcites →https://doi.org/10.1016/j.eswa.2016.10.043openalex-snapshot
Sentiment analysis leveraging emotions and word embeddings
inferredcites →https://doi.org/10.1016/j.ijinfomgt.2019.07.004openalex-snapshot
Social media opinion summarization using emotion cognition and convolutional neural networks
inferredcites →https://doi.org/10.1016/j.ijinfomgt.2020.102138openalex-snapshot
The role of emotion in P2P microfinance funding: A sentiment analysis approach
inferredcites →https://doi.org/10.1016/j.inffus.2018.03.007openalex-snapshot
Consensus vote models for detecting and filtering neutrality in sentiment analysis
inferredcites →https://doi.org/10.1016/j.inffus.2020.01.011openalex-snapshot
Emotion recognition using multi-modal data and machine learning techniques: A tutorial and review
inferredcites →https://doi.org/10.1016/j.ins.2013.12.059openalex-snapshot
Sentiment topic models for social emotion mining
inferredcites →https://doi.org/10.1016/j.ins.2017.02.004openalex-snapshot
A fuzzy computational model of emotion for cloud based sentiment analysis
inferredcites →https://doi.org/10.1016/j.ipm.2015.03.007openalex-snapshot
Onyx: A Linked Data approach to emotion representation
inferredcites →https://doi.org/10.1016/j.ipm.2015.10.003openalex-snapshot
Ontology-based affective models to organize artworks in the social semantic web
inferredcites →https://doi.org/10.1016/j.is.2008.07.002openalex-snapshot
A software engineering approach to ontology building
inferredcites →https://doi.org/10.1016/j.jbusres.2003.09.013openalex-snapshot
Emotions in consumer behavior: a hierarchical approach
inferredcites →https://doi.org/10.1016/j.jestch.2021.01.007openalex-snapshot
Market sentiment-aware deep reinforcement learning approach for stock portfolio allocation
inferredcites →https://doi.org/10.1016/j.jocs.2019.05.009openalex-snapshot
Emotion and sentiment analysis from Twitter text
inferredcites →https://doi.org/10.1016/j.knosys.2015.06.015openalex-snapshot
A survey on opinion mining and sentiment analysis: Tasks, approaches and applications
inferredcites →https://doi.org/10.1016/j.knosys.2018.11.018openalex-snapshot
Semi-supervised dimensional sentiment analysis with variational autoencoder
inferredcites →https://doi.org/10.1016/j.knosys.2019.02.033openalex-snapshot
Transportation sentiment analysis using word embedding and ontology-based topic modeling
inferredcites →https://doi.org/10.1016/j.knosys.2022.108586openalex-snapshot
Aspect-level sentiment classification based on attention-BiLSTM model and transfer learning
inferredcites →https://doi.org/10.1016/j.knosys.2022.108742openalex-snapshot
Investigating the informativeness of technical indicators and news sentiment in financial market price prediction
inferredcites →https://doi.org/10.1016/j.neucom.2015.01.095openalex-snapshot
Fusing audio, visual and textual clues for sentiment analysis from multimodal content
inferredcites →https://doi.org/10.1016/j.neucom.2018.05.104openalex-snapshot
Boosting image sentiment analysis with visual attention
inferredcites →https://doi.org/10.1016/j.neunet.2019.05.021openalex-snapshot
Hierarchical human-like strategy for aspect-level sentiment classification with sentiment linguistic knowledge and reinforcement learning
inferredcites →https://doi.org/10.1017/cbo9780511571299openalex-snapshot
The Cognitive Structure of Emotions
inferredcites →https://doi.org/10.1017/s0140525x00012759openalex-snapshot
Toward a general psychobiological theory of emotions
inferredcites →https://doi.org/10.1023/a:1013365332180openalex-snapshot
Modeling Multimodal Expression of User’s Affective Subjective Experience
inferredcites →https://doi.org/10.1037//0003-066x.48.4.384openalex-snapshot
Facial expression and emotion.
inferredcites →https://doi.org/10.1037//0022-3514.37.3.345openalex-snapshot
Affective space is bipolar.
inferredcites →https://doi.org/10.1037//0022-3514.53.4.712openalex-snapshot
Universals and cultural differences in the judgments of facial expressions of emotion.
inferredcites →https://doi.org/10.1037//0022-3514.53.4.751openalex-snapshot
The psychological foundations of the affective lexicon.
inferredcites →https://doi.org/10.1037//0022-3514.57.2.212openalex-snapshot
Relations among emotion, appraisal, and emotional action readiness.
inferredcites →https://doi.org/10.1037//0022-3514.69.1.153openalex-snapshot
Valence focus and arousal focus: Individual differences in the structure of affective experience.
inferredcites →https://doi.org/10.1037//0033-295x.110.1.145openalex-snapshot
Core affect and the psychological construction of emotion.
inferredcites →https://doi.org/10.1037//0033-295x.97.3.315openalex-snapshot
What's basic about basic emotions?
inferredcites →https://doi.org/10.1037/14351-000openalex-snapshot
Affect, imagery, consciousness, Vol. 1: The positive affects.
inferredcites →https://doi.org/10.1037/h0054570openalex-snapshot
Three dimensions of emotion.
inferredcites →https://doi.org/10.1037/h0077714openalex-snapshot
A circumplex model of affect.
inferredcites →https://doi.org/10.1057/9780230511910openalex-snapshot
The Language of Evaluation
inferredcites →https://doi.org/10.1057/jit.2010.1openalex-snapshot
SEMO: A Framework for Customer Social Networks Analysis Based on Semantics
inferredcites →https://doi.org/10.1080/02699930902928969openalex-snapshot
The dynamic architecture of emotion: Evidence for the component process model
inferredcites →https://doi.org/10.1080/02699938708408361openalex-snapshot
The Relationship of Emotion to Cognition: A Functional Approach to a Semantic Controversy
inferredcites →https://doi.org/10.1080/02699938708408362openalex-snapshot
Towards a Cognitive Theory of Emotions
inferredcites →https://doi.org/10.1080/02699939208411068openalex-snapshot
An argument for basic emotions
inferredcites →https://doi.org/10.1080/026999398379574openalex-snapshot
Discrete Emotions or Dimensions? The Role of Valence Focus and Arousal Focus
inferredcites →https://doi.org/10.1080/0929821042000317822openalex-snapshot
Which Emotions Can be Induced by Music? What Are the Underlying Mechanisms? And How Can We Measure Them?
inferredcites →https://doi.org/10.1080/0952813x.2014.971443openalex-snapshot
EOSentiMiner: an opinion-aware system based on emotion ontology for sentiment analysis of Chinese online reviews
inferredcites →https://doi.org/10.1080/10798587.2016.1267243openalex-snapshot
Building Ontology for Different Emotional Contexts and Multilingual Environment in Opinion Mining
inferredcites →https://doi.org/10.1086/209499openalex-snapshot
Measuring Emotions in the Consumption Experience
inferredcites →https://doi.org/10.1093/ietisy/e90-d.8.1262openalex-snapshot
Ontology-Based Context Modeling and Reasoning for U-HealthCare
inferredcites →https://doi.org/10.1093/oso/9780195069945.001.0001openalex-snapshot
Emotion And Adaptation
inferredcites →https://doi.org/10.1093/oso/9780195114645.003.0006openalex-snapshot
Psychological Models of Emotion
inferredcites →https://doi.org/10.1093/oso/9780195130072.001.0001openalex-snapshot
Appraisal Processes in Emotion
inferredcites →https://doi.org/10.1093/oso/9780195153170.001.0001openalex-snapshot
Thinking About Feeling
inferredcites →https://doi.org/10.1109/access.2018.2832137openalex-snapshot
Application of Sentiment Analysis to Language Learning
inferredcites →https://doi.org/10.1109/access.2019.2903436openalex-snapshot
Application of an Ontology-Based Platform for Developing Affective Interaction Systems
inferredcites →https://doi.org/10.1109/access.2020.2993803openalex-snapshot
Facial Sentiment Analysis Using AI Techniques: State-of-the-Art, Taxonomies, and Challenges
inferredcites →https://doi.org/10.1109/access.2020.3031217openalex-snapshot
A Systematic Review on Implicit and Explicit Aspect Extraction in Sentiment Analysis
inferredcites →https://doi.org/10.1109/acii.2009.5349538openalex-snapshot
Integration of a semantic and affective model for realistic generation of emotional states in virtual characters
inferredcites →https://doi.org/10.1109/aina.2018.00094openalex-snapshot
An Ontology-Based Approach for Mining Radicalization Indicators from Online Messages
inferredcites →https://doi.org/10.1109/cbmi.2010.5529906openalex-snapshot
Classification of affective semantics in images based on discrete and dimensional models of emotions
inferredcites →https://doi.org/10.1109/ccaa.2015.7148343openalex-snapshot
EmotionFinder: Detecting emotion from blogs and textual documents
inferredcites →https://doi.org/10.1109/cisis.2013.132openalex-snapshot
Building of Japanese Emotion Ontology from Knowledge on the Web for Realistic Interactive CG Characters
inferredcites →https://doi.org/10.1109/coginfocom.2013.6719313openalex-snapshot
Emotion ontology for context awareness
inferredcites →https://doi.org/10.1109/dest.2010.5610601openalex-snapshot
Multidimensional ontology modeling of human digital ecosystems affected by social behavioural data patterns
inferredcites →https://doi.org/10.1109/hicss.2016.246openalex-snapshot
Measuring Emotion Bifurcation Points for Individuals in Social Media
inferredcites →https://doi.org/10.1109/icds.2009.50openalex-snapshot
Music Ontology for Mood and Situation Reasoning to Support Music Retrieval and Recommendation
inferredcites →https://doi.org/10.1109/ictai.2011.165openalex-snapshot
Lyrics-Based Emotion Classification Using Feature Selection by Partial Syntactic Analysis
inferredcites →https://doi.org/10.1109/ie.2012.13openalex-snapshot
The Nonverbal Toolkit: Towards a Framework for Automatic Integration of Nonverbal Communication into Virtual Environments
inferredcites →https://doi.org/10.1109/incos.2015.78openalex-snapshot
An Ontology about Emotion Awareness and Affective Feedback in Elearning
inferredcites →https://doi.org/10.1109/is.2018.8710542openalex-snapshot
CADAP: A student’s emotion monitoring solution for e-learning performance analysis
inferredcites →https://doi.org/10.1109/iwsca.2008.36openalex-snapshot
OntoSonomy: Ontology-Based Extension of Folksonomy
inferredcites →https://doi.org/10.1109/mci.2019.2901082openalex-snapshot
Computational Intelligence for Affective Computing and Sentiment Analysis [Guest Editorial]
inferredcites →https://doi.org/10.1109/mis.2010.151openalex-snapshot
Social Media Analytics and Intelligence
inferredcites →https://doi.org/10.1109/mis.2013.30openalex-snapshot
New Avenues in Opinion Mining and Sentiment Analysis
inferredcites →https://doi.org/10.1109/mis.2016.31openalex-snapshot
Affective Computing and Sentiment Analysis
inferredcites →https://doi.org/10.1109/mis.2016.94openalex-snapshot
Multimodal Sentiment Intensity Analysis in Videos: Facial Gestures and Verbal Messages
inferredcites →https://doi.org/10.1109/mis.2017.23openalex-snapshot
Deep Learning-Based Document Modeling for Personality Detection from Text
inferredcites →https://doi.org/10.1109/mis.2017.57openalex-snapshot
Aspect-Based Extraction and Analysis of Affective Knowledge from Social Media Streams
inferredcites →https://doi.org/10.1109/mis.2018.033001419openalex-snapshot
OntoSenticNet: A Commonsense Ontology for Sentiment Analysis
inferredcites →https://doi.org/10.1109/mis.2018.043741326openalex-snapshot
Detecting Personal Intake of Medicine from Twitter
inferredcites →https://doi.org/10.1109/mis.2018.2877279openalex-snapshot
No, That Never Happened!! Investigating Rumors on Twitter
inferredcites →https://doi.org/10.1109/mis.2018.2882362openalex-snapshot
Multimodal Sentiment Analysis: Addressing Key Issues and Setting Up the Baselines
inferredcites →https://doi.org/10.1109/mis.2019.2899143openalex-snapshot
Supervised Learning for Fake News Detection
inferredcites →https://doi.org/10.1109/mis.2019.2904691openalex-snapshot
Sentiment and Sarcasm Classification With Multitask Learning
inferredcites →https://doi.org/10.1109/mis.2020.2992799openalex-snapshot
The Hourglass Model Revisited
inferredcites →https://doi.org/10.1109/mis.2021.3062475openalex-snapshot
This! Identifying New Sentiment Slang Through Orthographic Pleonasm Online: Yasss Slay Gorg Queen Ilysm
inferredcites →https://doi.org/10.1109/mis.2021.3093659openalex-snapshot
OntoSenticNet 2: Enhancing Reasoning Within Sentiment Analysis
inferredcites →https://doi.org/10.1109/t-affc.2011.22openalex-snapshot
Generation of Personalized Ontology Based on Consumer Emotion and Behavior Analysis
inferredcites →https://doi.org/10.1109/t-affc.2011.33openalex-snapshot
Building and Exploiting EmotiNet, a Knowledge Base for Emotion Detection Based on the Appraisal Theory Model
inferredcites →https://doi.org/10.1109/taai.2015.7407096openalex-snapshot
SentiWordSKOS: A lexical ontology extended with sentiments and emotions
inferredcites →https://doi.org/10.1109/taffc.2014.2317187openalex-snapshot
Are They Different? Affect, Feeling, Emotion, Sentiment, and Opinion Detection in Text
inferredcites →https://doi.org/10.1109/taffc.2015.2444846openalex-snapshot
Sentiment Analysis: From Opinion Mining to Human-Agent Interaction
inferredcites →https://doi.org/10.1109/taffc.2019.2926724openalex-snapshot
All-in-One: Emotion, Sentiment and Intensity Prediction Using a Multi-Task Ensemble Framework
inferredcites →https://doi.org/10.1109/taffc.2020.2970399openalex-snapshot
Issues and Challenges of Aspect-based Sentiment Analysis: A Comprehensive Survey
inferredcites →https://doi.org/10.1109/tcsvt.2021.3072412openalex-snapshot
Real-Time Video Emotion Recognition Based on Reinforcement Learning and Domain Knowledge
inferredcites →https://doi.org/10.1109/tkde.2015.2485209openalex-snapshot
Survey on Aspect-Level Sentiment Analysis
inferredcites →https://doi.org/10.1109/tmc.2018.2879864openalex-snapshot
EGO: Optimized Sensor Selection for Multi-Context Aware Applications with an Ontology for Recognition Models
inferredcites →https://doi.org/10.1109/tmm.2004.840618openalex-snapshot
Affective video content representation and modeling
inferredcites →https://doi.org/10.1109/waci.2011.5953153openalex-snapshot
An ontology for predicting students' emotions during a quiz. Comparison with self-reported emotions
inferredcites →https://doi.org/10.1111/j.0956-7976.2004.01503008.xopenalex-snapshot
Show Your Pride
inferredcites →https://doi.org/10.1111/j.1467-8640.2012.00458.xopenalex-snapshot
A BOOTSTRAPPING METHOD FOR EXTRACTING PARAPHRASES OF EMOTION EXPRESSIONS FROM TEXTS
inferredcites →https://doi.org/10.1111/j.1467-8640.2012.00460.xopenalex-snapshot
CROWDSOURCING A WORD–EMOTION ASSOCIATION LEXICON
inferredcites →https://doi.org/10.1111/j.1467-9280.2007.02024.xopenalex-snapshot
The World of Emotions is not Two-Dimensional
inferredcites →https://doi.org/10.1111/j.1469-8986.1979.tb01511.xopenalex-snapshot
A Bio‐Informational Theory of Emotional Imagery
inferredcites →https://doi.org/10.1111/jcal.12247openalex-snapshot
Improving early prediction of academic failure using sentiment analysis on self‐evaluated comments
inferredcites →https://doi.org/10.1142/s0218488520500294openalex-snapshot
Multi-Level Fine-Scaled Sentiment Sensing with Ambivalence Handling
inferredcites →https://doi.org/10.1145/1165255.1165259openalex-snapshot
Emotion recognition from text using semantic labels and separable mixture models
inferredcites →https://doi.org/10.1145/1352694.1352741openalex-snapshot
Ontology Based Affective Context Representation
inferredcites →https://doi.org/10.1145/1363686.1364052openalex-snapshot
Learning to identify emotions in text
inferredcites →https://doi.org/10.1145/2070481.2070509openalex-snapshot
Towards multimodal sentiment analysis
inferredcites →https://doi.org/10.1145/2502069.2502071openalex-snapshot
Combining strengths, emotions and polarities for boosting Twitter sentiment analysis
inferredcites →https://doi.org/10.1145/2502081.2502282openalex-snapshot
Large-scale visual sentiment ontology and detectors using adjective noun pairs
inferredcites →https://doi.org/10.1145/2733373.2806246openalex-snapshot
Visual Affect Around the World
inferredcites →https://doi.org/10.1145/2911996.2912030openalex-snapshot
Complura
inferredcites →https://doi.org/10.1145/3057270openalex-snapshot
Current State of Text Sentiment Analysis from Opinion to Emotion Mining
inferredcites →https://doi.org/10.1145/3124420openalex-snapshot
Automatic Sarcasm Detection
inferredcites →https://doi.org/10.1145/3329124openalex-snapshot
Evaluating Domain Ontologies
inferredcites →https://doi.org/10.1145/3340531.3412003openalex-snapshot
SenticNet 6: Ensemble Application of Symbolic and Subsymbolic AI for Sentiment Analysis
inferredcites →https://doi.org/10.1145/3369026openalex-snapshot
Stance Detection
inferredcites →https://doi.org/10.1145/3372152openalex-snapshot
Emo2Vec
inferredcites →https://doi.org/10.1145/3439726openalex-snapshot
Deep Learning--based Text Classification
inferredcites →https://doi.org/10.1146/annurev.ps.43.020192.000415openalex-snapshot
Human Emotions: Function And Dysfunction
inferredcites →https://doi.org/10.1146/annurev.psych.60.110707.163539openalex-snapshot
Emotion Theory and Research: Highlights, Unanswered Questions, and Emerging Issues
inferredcites →https://doi.org/10.1155/2018/8071251openalex-snapshot
Mobile Personalized Service Recommender Model Based on Sentiment Analysis and Privacy Concern
inferredcites →https://doi.org/10.1177/0539018405058216openalex-snapshot
What are emotions? And how can they be measured?
inferredcites →https://doi.org/10.1177/1754073912445818openalex-snapshot
Toward a Working Definition of Emotion
showing the first 200 of 245 · page through all 245

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-031-75589-7_8openalex-snapshot
AI and Customer Experience: Personalization and Engagement in Middle Eastern Markets
inferred← citeshttps://doi.org/10.1007/978-3-032-12888-1_42openalex-snapshot
Patterns Beyond Words: Understanding Emotional Undertone on Knowledge Graphs
inferred← citeshttps://doi.org/10.1007/978-3-032-40774-0_32openalex-snapshot
An Ontology-Grounded Knowledge Graph Framework for Personalized and Explainable Emotional Support in Conversational Systems
inferred← citeshttps://doi.org/10.1007/978-981-97-5098-6_13openalex-snapshot
A Real-Time Impact Study of New Product Release on Theme Park Brand Reputation: Using Social Media Data from Shanghai Disneyland
inferred← citeshttps://doi.org/10.1007/s10207-025-01136-7openalex-snapshot
Enhancing national security: a multidimensional situational awareness model for emerging economic crime prevention
inferred← citeshttps://doi.org/10.1007/s10796-025-10623-0openalex-snapshot
Tabloids, Fake News, and the Overton Window: The COP Model on News Consumption in Uncertain Times
inferred← citeshttps://doi.org/10.1016/j.jvcir.2025.104427openalex-snapshot
Dynamic emotional memory analysis in digital animation via expression recognition and scene atmosphere enhancement
inferred← citeshttps://doi.org/10.1016/j.sasc.2026.200487openalex-snapshot
Sentiment orientation classification of Chinese internet public opinion analysis on the stock market based on Baidu NLP
inferred← citeshttps://doi.org/10.1016/j.ufug.2026.129460openalex-snapshot
Emotional landscapes: Mapping urban park sentiments using natural language processing
inferred← citeshttps://doi.org/10.1080/21645515.2023.2278377openalex-snapshot
Longitudinal analysis of behavioral factors and techniques used to identify vaccine hesitancy among Twitter users: Scoping review
inferred← citeshttps://doi.org/10.1097/md.0000000000042904openalex-snapshot
Drug–drug interaction analysis based on information bottleneck graph neural network: A review
inferred← citeshttps://doi.org/10.1108/oir-03-2024-0192openalex-snapshot
Multi-level emotion propagation in natural disaster events: diverse leadership of super-spreaders in different levels of hierarchy
inferred← citeshttps://doi.org/10.1109/icc-robins60238.2024.10533989openalex-snapshot
Machine learning-based Sentiment Analysis: A Comprehensive Review
inferred← citeshttps://doi.org/10.1109/icidca56705.2023.10100082openalex-snapshot
Evaluating the Impact of Sentiments in Decision Making: A Review
inferred← citeshttps://doi.org/10.1109/ictacs59847.2023.10390141openalex-snapshot
Unraveling Ambivalence: A Novel Approach for Sarcasm Detection in Sentiment Analysis
inferred← citeshttps://doi.org/10.1109/paee71887.2026.11660668openalex-snapshot
Performance and Efficiency Analysis of Classifiers for Sentiment and Emotion Detection
inferred← citeshttps://doi.org/10.1109/sist61657.2025.11139242openalex-snapshot
LLM Agents for Enhanced Tabular Data Interpretation: A Perspective
inferred← citeshttps://doi.org/10.1109/taffc.2025.3649246openalex-snapshot
Sifting Truth From Spectacle! A Multimodal Hindi Dataset for Misinformation Detection With Emotional Cues and Sentiments
inferred← citeshttps://doi.org/10.1145/3744169.3744174openalex-snapshot
Sticking with Affect in HCI and Design: from Interaction to Relation
inferred← citeshttps://doi.org/10.1177/14727978251316402openalex-snapshot
Construction of financial fraud identification model based on stacking and accounting indicators
inferred← citeshttps://doi.org/10.1186/s40359-024-02008-wopenalex-snapshot
Evaluation of emotion classification schemes in social media text: an annotation-based approach
inferred← citeshttps://doi.org/10.1186/s43093-026-00764-2openalex-snapshot
Public sentiment and economic uncertainty: an exploratory analysis of Twitter discourse on the anticipated 2023 recession
inferred← citeshttps://doi.org/10.14421/ijid.2024.4176openalex-snapshot
Leveraging Ontology-Driven Machine Learning for Public Policy Analysis: A Systematic Review of Social Media Applications
inferred← citeshttps://doi.org/10.26599/bdma.2024.9020092openalex-snapshot
Text Classification Techniques: A Holistic Review, Observational Analysis, and Experimental Investigation
inferred← citeshttps://doi.org/10.32604/cmc.2024.056215openalex-snapshot
Integrating Ontology-Based Approaches with Deep Learning Models for Fine-Grained Sentiment Analysis
inferred← citeshttps://doi.org/10.3390/info15080468openalex-snapshot
VoiceBack: Design of Artificial Intelligence-Driven Voice-Based Feedback System for Customer-Agency Communication in Online Travel Services
inferred← citeshttps://doi.org/10.4018/979-8-3693-1082-3.ch014openalex-snapshot
Applications of Pipelining With ML to Authenticate Emotions in Textual Contents
inferred← citeshttps://doi.org/10.4018/joeuc.388646openalex-snapshot
The Impact of Social Media Information Dissemination on Consumer Brand Perception
inferred← citeshttps://doi.org/10.52726/as.humanities/2023.4.8openalex-snapshot
ОСОБЛИВОСТІ НЕЙРОМЕРЕЖЕВОГО МОДЕЛЮВАННЯ ПРОЦЕСІВ РОЗПІЗНАВАННЯ ЛІНГВІСТИЧНИХ МАРКЕРІВ КАТЕГОРІЙ СМИСЛУ ТА АБСУРДУ В КОНТЕКСТІ РОБОТИ З НЕПРАВДИВИМИ ДАНИМИ
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.