On the public citation graph

Balancing Prediction Errors for Robust Sentiment Classification

https://doi.org/10.1145/3328795
0 signed · 47 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.

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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.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/asi.21662openalex-snapshot
Sentiment strength detection for the social web
inferredcites →https://doi.org/10.1007/978-3-319-43639-5_7openalex-snapshot
The Heart and Soul of the Web? Sentiment Strength Detection in the Social Web with SentiStrength
inferredcites →https://doi.org/10.1007/s10618-010-0190-xopenalex-snapshot
Three naive Bayes approaches for discrimination-free classification
inferredcites →https://doi.org/10.1016/j.ins.2017.09.064openalex-snapshot
Exploiting reject option in classification for social discrimination control
inferredcites →https://doi.org/10.1016/j.ipm.2009.03.002openalex-snapshot
A systematic analysis of performance measures for classification tasks
inferredcites →https://doi.org/10.1016/j.patcog.2007.04.009openalex-snapshot
Cost-sensitive boosting for classification of imbalanced data
inferredcites →https://doi.org/10.1109/icdm.2012.45openalex-snapshot
Decision Theory for Discrimination-Aware Classification
inferredcites →https://doi.org/10.1109/icdmw.2011.83openalex-snapshot
Fairness-aware Learning through Regularization Approach
inferredcites →https://doi.org/10.1109/icsmc.2012.6378300openalex-snapshot
An empirical study to address the problem of Unbalanced Data Sets in sentiment classification
inferredcites →https://doi.org/10.1109/tkde.2008.239openalex-snapshot
Learning from Imbalanced Data
inferredcites →https://doi.org/10.1109/tsmcb.2008.2002909openalex-snapshot
SVMs Modeling for Highly Imbalanced Classification
inferredcites →https://doi.org/10.1145/1401890.1401959openalex-snapshot
Discrimination-aware data mining
inferredcites →https://doi.org/10.1145/2020408.2020488openalex-snapshot
k-NN as an implementation of situation testing for discrimination discovery and prevention
inferredcites →https://doi.org/10.1145/2063576.2063994openalex-snapshot
Imbalanced sentiment classification
inferredcites →https://doi.org/10.1145/2512938.2512951openalex-snapshot
Comparing and combining sentiment analysis methods
inferredcites →https://doi.org/10.1145/2695664.2695759openalex-snapshot
Bias-aware lexicon-based sentiment analysis
inferredcites →https://doi.org/10.1177/0261927x09351676openalex-snapshot
The Psychological Meaning of Words: LIWC and Computerized Text Analysis Methods
inferredcites →https://doi.org/10.1609/icwsm.v5i1.14171openalex-snapshot
Modeling Public Mood and Emotion: Twitter Sentiment and Socio-Economic Phenomena
inferredcites →https://doi.org/10.1613/jair.953openalex-snapshot
SMOTE: Synthetic Minority Over-sampling Technique
inferredcites →https://doi.org/10.3115/1218955.1218990openalex-snapshot
A sentimental education
inferredcites →https://doi.org/10.4230/lipics.mfcs.2021.56openalex-snapshot
Obstructing Classification via Projection
inferredcites →https://doi.org/10.48550/arxiv.1505.05723openalex-snapshot
On the relation between accuracy and fairness in binary classification
inferredcites →https://doi.org/10.48550/arxiv.1606.07558openalex-snapshot
Satisfying Real-world Goals with Dataset Constraints

What points at this work

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

inferred← citeshttps://doi.org/10.1007/978-3-030-53980-1_124openalex-snapshot
An Analysis Method of User Group’s Emotional Tendency in Hot Topic of Microblog
inferred← citeshttps://doi.org/10.1007/978-3-031-76459-2_2openalex-snapshot
Adversarial Evasion Attack Efficiency Against Large Language Models
inferred← citeshttps://doi.org/10.1016/j.autcon.2020.103479openalex-snapshot
Computer-assisted separation of design-build contract requirements to support subcontract drafting
inferred← citeshttps://doi.org/10.1108/ijilt-04-2025-0121openalex-snapshot
Mapping AI feedback under emotional prompts: a sentiment-topic-network approach
inferred← citeshttps://doi.org/10.1109/access.2020.3014849openalex-snapshot
An Unsupervised Sentiment Classification Method Based on Multi-Level Fuzzy Computing and Multi-Criteria Fusion
inferred← citeshttps://doi.org/10.1109/tai.2022.3160658openalex-snapshot
On Supervised Class-Imbalanced Learning: An Updated Perspective and Some Key Challenges
inferred← citeshttps://doi.org/10.1109/wccct69960.2026.11549734openalex-snapshot
A Multilingual Intersectional Bias Framework For Detecting and Mitigating Demographic Bias In Sentiment Classification
inferred← citeshttps://doi.org/10.1142/s0219622022500584openalex-snapshot
Opinion Mining Using Enriched Joint Sentiment-Topic Model
inferred← citeshttps://doi.org/10.1145/3632529openalex-snapshot
Causality-Based Fair Multiple Decision by Response Functions
inferred← citeshttps://doi.org/10.1145/3638353openalex-snapshot
Graph-based Text Classification by Contrastive Learning with Text-level Graph Augmentation
inferred← citeshttps://doi.org/10.1155/2021/8135942openalex-snapshot
Recognition of Psychological Characteristics of Students’ Behavior Based on Improved Machine Learning
inferred← citeshttps://doi.org/10.1155/2022/7612276openalex-snapshot
Weighted Joint Sentiment-Topic Model for Sentiment Analysis Compared to ALGA: Adaptive Lexicon Learning Using Genetic Algorithm
inferred← citeshttps://doi.org/10.1177/16094069211002413openalex-snapshot
The Happy Level: A New Approach to Measure Happiness at Work Using Mixed Methods
inferred← citeshttps://doi.org/10.3233/jifs-189227openalex-snapshot
Student sentiment classification model based on GRU neural network and TF-IDF algorithm
inferred← citeshttps://doi.org/10.3233/jifs-189413openalex-snapshot
Students’ emotional analysis on ideological and political teaching classes based on artificial intelligence and data mining
inferred← citeshttps://doi.org/10.3233/jifs-219039openalex-snapshot
Research on the influence of music educational psychology on saxophone players’ mental state and stage performance
inferred← citeshttps://doi.org/10.3233/jifs-219040openalex-snapshot
Music psychology using fuzzy models to promote mental health
inferred← citeshttps://doi.org/10.3233/jifs-219047openalex-snapshot
Sentiment analysis of students in ideological and political teaching based on artificial intelligence and data mining
inferred← citeshttps://doi.org/10.3233/jifs-219048openalex-snapshot
Research on the data analysis system of student stress in English MOOC based on fuzzy C-means algorithm
inferred← citeshttps://doi.org/10.3233/jifs-219050openalex-snapshot
The system for relieving students’ boring emotion in English learning based on fuzzy neural network
inferred← citeshttps://doi.org/10.3233/jifs-219053openalex-snapshot
Evaluation of the effect of music education on improving students’ mental health based on intelligent fuzzy system
inferred← citeshttps://doi.org/10.3233/jifs-219057openalex-snapshot
The music psychology that uses fuzzy models to promote mental health
inferred← citeshttps://doi.org/10.3233/jifs-219161openalex-snapshot
Students’ emotion recognition and psychological stress during the exam
inferred← citeshttps://doi.org/10.62441/nano-ntp.vi.5447openalex-snapshot
Fine Tuning Llm For Sentiment Analysis
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.