SOTAVerified

Sentiment Analysis

Sentiment Analysis is the task of classifying the polarity of a given text. For instance, a text-based tweet can be categorized into either "positive", "negative", or "neutral". Given the text and accompanying labels, a model can be trained to predict the correct sentiment.

Sentiment Analysis techniques can be categorized into machine learning approaches, lexicon-based approaches, and even hybrid methods. Some subcategories of research in sentiment analysis include: multimodal sentiment analysis, aspect-based sentiment analysis, fine-grained opinion analysis, language specific sentiment analysis.

More recently, deep learning techniques, such as RoBERTa and T5, are used to train high-performing sentiment classifiers that are evaluated using metrics like F1, recall, and precision. To evaluate sentiment analysis systems, benchmark datasets like SST, GLUE, and IMDB movie reviews are used.

Further readings:

Papers

Showing 55515600 of 5630 papers

TitleStatusHype
Social Event Radar: A Bilingual Context Mining and Sentiment Analysis Summarization System0
Deep Learning for NLP (without Magic)0
UWN: A Large Multilingual Lexical Knowledge Base0
Subgroup Detector: A System for Detecting Subgroups in Online Discussions0
Fine Granular Aspect Analysis using Latent Structural Models0
A System for Real-time Twitter Sentiment Analysis of 2012 U.S. Presidential Election Cycle0
Cross-Lingual Mixture Model for Sentiment Classification0
A Broad-Coverage Normalization System for Social Media Language0
A Comparison of Chinese Parsers for Stanford Dependencies0
Humor as Circuits in Semantic Networks0
Polarity Consistency Checking for Sentiment Dictionaries0
Cross-Domain Co-Extraction of Sentiment and Topic Lexicons0
Baselines and Bigrams: Simple, Good Sentiment and Topic Classification0
Subgroup Detection in Ideological Discussions0
Aspect Extraction through Semi-Supervised Modeling0
Information-theoretic Multi-view Domain Adaptation0
Propagation de polarit\'es dans des familles de mots : impact de la morphologie dans la construction d'un lexique pour l'analyse de sentiments (Spreading Polarities among Word Families: Impact of Morphology on Building a Lexicon for Sentiment Analysis) [in French]0
Sur l'application de m\'ethodes textom\'etriques \`a la construction de crit\`eres de classification en analyse des sentiments (About the application of textometric methods for developing classi!cation criteria in Sentiment analysis) [in French]0
ResTS : Syst\`eme de R\'esum\'e Automatique des Textes d'Opinions bas\'e sur Twitter et SentiWordNet (System of Customer Review Summarization using Twitter and SentiWordNet) [in French]0
廣義知網詞彙意見極性的預測 (Predicting the Semantic Orientation of Terms in E-HowNet) [In Chinese]0
Analyzing Urdu Social Media for Sentiments using Transfer Learning with Controlled Translations0
Re-tweeting from a linguistic perspective0
100 Things You Always Wanted to Know about Linguistics But Were Afraid to Ask*0
AttitudeMiner: Mining Attitude from Online Discussions0
Behavioral Factors in Interactive Training of Text ClassifiersCode1
On-Demand Distributional Semantic Distance and Paraphrasing0
Minimum-Risk Training of Approximate CRF-Based NLP Systems0
Learning from Bullying Traces in Social Media0
Context-Enhanced Citation Sentiment Detection0
Grammatical structures for word-level sentiment detection0
A Graphical User Interface for Feature-Based Opinion Mining0
Extending the EmotiNet Knowledge Base to Improve the Automatic Detection of Implicitly Expressed Emotions from Text0
AWATIF: A Multi-Genre Corpus for Modern Standard Arabic Subjectivity and Sentiment Analysis0
The Political Speech Corpus of Bulgarian0
Building a fine-grained subjectivity lexicon from a web corpus0
A data and analysis resource for an experiment in text mining a collection of micro-blogs on a political topic.0
A Database of Attribution Relations0
Assigning Connotation Values to Events0
Yes we can!? Annotating English modal verbs0
Learning Sentiment Lexicons in Spanish0
Fine-grained German Sentiment Analysis on Social Media0
Linguagrid: a network of Linguistic and Semantic Services for the Italian Language.0
Affective Common Sense Knowledge Acquisition for Sentiment Analysis0
Hindi Subjective Lexicon: A Lexical Resource for Hindi Adjective Polarity Classification0
Quantising Opinions for Political Tweets Analysis0
Modality in Text: a Proposal for Corpus Annotation0
Cost and Benefit of Using WordNet Senses for Sentiment Analysis0
``Vreselijk mooi!'' (terribly beautiful): A Subjectivity Lexicon for Dutch Adjectives.0
Annotating Opinions in German Political News0
Automatic word alignment tools to scale production of manually aligned parallel texts0
Show:102550
← PrevPage 112 of 113Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Word+ES (Scratch)Attack Success Rate100Unverified
2MT-DNN-SMARTAccuracy97.5Unverified
3T5-11BAccuracy97.5Unverified
4MUPPET Roberta LargeAccuracy97.4Unverified
5T5-3BAccuracy97.4Unverified
6ALBERTAccuracy97.1Unverified
7StructBERTRoBERTa ensembleAccuracy97.1Unverified
8XLNet (single model)Accuracy97Unverified
9SMARTRoBERTaDev Accuracy96.9Unverified
10ELECTRAAccuracy96.9Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTa-large with LlamBERTAccuracy96.68Unverified
2RoBERTa-largeAccuracy96.54Unverified
3XLNetAccuracy96.21Unverified
4Heinsen Routing + RoBERTa LargeAccuracy96.2Unverified
5RoBERTa-large 355M + Entailment as Few-shot LearnerAccuracy96.1Unverified
6GraphStarAccuracy96Unverified
7DV-ngrams-cosine with NB sub-sampling + RoBERTa.baseAccuracy95.94Unverified
8DV-ngrams-cosine + RoBERTa.baseAccuracy95.92Unverified
9Roberta_Large ST + Cosine Similarity LossAccuracy95.9Unverified
10BERT large finetune UDAAccuracy95.8Unverified
#ModelMetricClaimedVerifiedStatus
1Llama-3.3-70B + CAPOAccuracy62.27Unverified
2Mistral-Small-24B + CAPOAccuracy 60.2Unverified
3Heinsen Routing + RoBERTa LargeAccuracy59.8Unverified
4RoBERTa-large+Self-ExplainingAccuracy59.1Unverified
5Qwen2.5-32B + CAPOAccuracy 59.07Unverified
6Heinsen Routing + GPT-2Accuracy58.5Unverified
7BCN+Suffix BiLSTM-Tied+CoVeAccuracy56.2Unverified
8BERT LargeAccuracy55.5Unverified
9LM-CPPF RoBERTa-baseAccuracy54.9Unverified
10BCN+ELMoAccuracy54.7Unverified
#ModelMetricClaimedVerifiedStatus
1Char-level CNNError4.88Unverified
2SVDCNNError4.74Unverified
3LEAMError4.69Unverified
4fastText, h=10, bigramError4.3Unverified
5SWEM-hierError4.19Unverified
6SRNNError3.96Unverified
7M-ACNNError3.89Unverified
8DNC+CUWError3.6Unverified
9CCCapsNetError3.52Unverified
10Block-sparse LSTMError3.27Unverified
#ModelMetricClaimedVerifiedStatus
1Millions of EmojiTraining Time1,500Unverified
2VLAWEAccuracy93.3Unverified
3RoBERTa-large 355M + Entailment as Few-shot LearnerAccuracy92.5Unverified
4AnglE-LLaMA-7BAccuracy91.09Unverified
5byte mLSTM7Accuracy86.8Unverified
6MEANAccuracy84.5Unverified
7RNN-CapsuleAccuracy83.8Unverified
8Capsule-BAccuracy82.3Unverified
9SuBiLSTM-TiedAccuracy81.6Unverified
10USE_T+CNNAccuracy81.59Unverified