We investigate cross-lingual sentiment analysis, which has attracted significant attention due to its applications in various areas including market research, politics and social sciences. In particular, we introduce a sentiment analysis framework in multi-label setting as it obeys Plutchik's wheel of emotions. We introduce a novel dynamic weighting method that balances the contribution from each class during training, unlike previous static weighting methods that assign non-changing weights based on their class frequency. Moreover, we adapt the focal loss that favors harder instances from single-label object recognition literature to our multi-label setting. Furthermore, we derive a method to choose optimal class-specific thresholds that maximize the macro-f1 score in linear time complexity. Through an extensive set of experiments, we show that our method obtains the state-of-the-art performance in 7 of 9 metrics in 3 different languages using a single model compared to the common baselines and the best-performing methods in the SemEval competition. We publicly share our code for our model, which can perform sentiment analysis in 100 languages, to facilitate further research.
A Failure of Aspect Sentiment Classifiers and an Adaptive Re-weighting Solution
Tsinghua University（清华大学）；University of Illinois at Chicago（伊利诺伊大学芝加哥分校）
基于情感的情感分类（ASC）是细粒度情感分析中的一个重要任务。深度监督ASC方法通常将此任务建模为成对分类任务，该成对分类任务采用方面和包含该方面的句子，并输出该句子中方面的极性。然而，我们发现许多现有的方法无法学习有效的ASC分类器，而更像是一个句子级别的情感分类器，因为它们很难处理不同方面的不同极性的句子。本文首先证明了这个问题，使用几个国家的最先进的ASC模型。然后，它提出了一种新的和通用的自适应重新加权（ARW）计划，以调整训练，以显着提高ASC这样的复杂句子。实验结果表明，该框架是有效的\footnote{The dataset and code are available at \url{https://github.com/howardhsu/ASC_failure}.} .
Adaptive Data Augmentation for Aspect Sentiment Quad Prediction
Institute of Information Engineering, Chinese Academy of Sciences（中国科学院信息工程研究所）；School of Cyber Security, University of Chinese Academy of Sciences（中国科学院大学网络空间安全学院）
GRACE: Gradient Harmonized and Cascaded Labeling for Aspect-based Sentiment Analysis
School of Information Science and Technology, Southwest Jiaotong University, China（西南交通大学信息科学与技术学院）；Microsoft Research Asia, Beijing, China（微软亚洲研究院，北京）；Institute of Computing Technology, Chinese Academy of Science, Beijing, China（中国科学院计算技术研究所，北京）；University of Chinese Academy of Sciences, Beijing, China（中国科学院大学，北京）；STCA NLP Group, Microsoft, Beijing, China（微软STCA自然语言处理组，北京）；Work is done during an internship at MSR Asia.（微软亚洲研究院实习（该句为实习说明，非机构名，按要求不应提取，此处修正））
在本文中，我们专注于不平衡的问题，这是很少研究的方面的条款提取和方面的情感分类时，将其视为序列标记任务。此外，以前的工作在标记极性时通常忽略体术语之间的相互作用。我们提出了一个GRadient hArmonized and CascadEd labeling model（GRACE）来解决这些问题。具体而言，级联标记模块的开发，以增强方面的条款之间的交换，并提高注意力的情感标记时，情感极性。极性序列被设计为取决于所生成的方面项标签。为了缓解不平衡的问题，我们扩展了梯度协调机制中使用的目标检测到基于方面的情感分析通过动态调整每个标签的权重。建议GRACE采用后预训练BERT作为其骨干。实验结果表明，该模型在多个基准数据集上实现了一致性改进，并产生了最先进的结果。
The Illusion of Balanced Multimodal Sentiment Analysis: Beyond the Limits of Optimization-Based Methods
Mines Paris-PSL University（巴黎高科矿业学院）；University of Bern（伯尔尼大学）；National Technical University of Athens（雅典国立技术大学）；Archimedes AI（阿基米德人工智能公司）；Synaptic Bloom PBC（Synaptic Bloom公益公司）
Multi-refined Feature Enhanced Sentiment Analysis Using Contextual Instruction
School of Computer Science and Engineering, University of Electronic Science and Technology of China（计算机科学与工程学院，电子科学与技术大学）；Southwestern University of Finance and Economics（西南财经大学）；Tongji University（同济大学）
Sentiment Analysis based Multi-person Multi-criteria Decision Making Methodology using Natural Language Processing and Deep Learning for Smarter Decision Aid. Case study of restaurant choice using TripAdvisor reviews
Andalusian Research Institute in Data Science and Computational Intelligence（安达卢西亚数据科学与计算智能研究所）；University of Granada（格拉纳达大学）
Detecting Abnormal User Feedback Patterns through Temporal Sentiment Aggregation
Khoury College of Computer Science Northeastern University Boston, United States；College of Engineering Northeastern University Boston, United States；College of Professional Studies Northeastern University Boston, United States
A Unified BERT-CNN-BiLSTM Framework for Simultaneous Headline Classification and Sentiment Analysis of Bangla News
Department of CCE, International Islamic University Chittagong（国际伊斯兰大学丘拉图加冈分校计算机工程系）；Department of ICE, Noakhali Science and Technology University（诺阿克利科学与技术大学信息工程系）；Department of CSE, Banladesh University of Engineering and Technology（孟加拉工程与技术大学计算机科学与工程系）；Dept. of CSE, IIUC, Chattogram, Bangladesh（国际伊斯兰大学丘拉图加冈分校计算机科学与工程系）；School of CSE, University of Southern Mississippi（密西西比大学南方分校计算机科学学院）；Department of CSE, Netrokona University（纳特罗克纳大学计算机科学与工程系）；mPower Social Enterprise（mPower社会企业）
A meta-analysis on the performance of machine-learning based language models for sentiment analysis
Institute of Sociology, Faculty of Social Sciences University of Duisburg-Essen（杜伊斯堡-埃森大学社会学院）；Department of Research & Development, Statistics Netherlands (CBS)（荷兰统计局（CBS）研究与发展部门）；IT.NRW – Statistical Office of NRW（北莱茵-威斯特法伦统计局）
A Case Study of Spanish Text Transformations for Twitter Sentiment Analysis
INFOTEC Centro de Investigación e Innovación en Tecnologías de la Información y Comunicación（INFOTEC 信息与通信技术研究与创新中心）；CentroGEO Centro de Investigación en Ciencias de Información Geoespacial（CentroGEO 地理空间信息科学研究中心）；CONACyT Consejo Nacional de Ciencia y Tecnología（国家科学技术委员会）
Enhance-then-Balance Modality Collaboration for Robust Multimodal Sentiment Analysis
Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University（航天信息安全部门与可信计算教育部重点实验室，网络安全科学与工程学院，武汉大学）
A Study on the Ambiguity in Human Annotation of German Oral History Interviews for Perceived Emotion Recognition and Sentiment Analysis
Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS)（弗劳恩霍夫智能分析与信息系统研究所）；Haus der Geschichte der Bundesrepublik Deutschland Foundation (HdG)（德意志联邦共和国历史之家基金会）；University of Applied Sciences Bonn-Rhein-Sieg（波恩-莱茵-锡格应用技术大学）；Autonomous Intelligent Systems (AIS), Computer Science Institute VI, Univ. of Bonn（波恩大学计算机科学第六研究所自主智能系统）
Automatic feature selection and weighting in molecular systems using Differentiable Information Imbalance
International School for Advanced Studies (SISSA)（国际高等研究院（SISSA））；The Institute of Science and Technology Austria (ISTA)（奥地利科学技术研究所）；University of Cal（卡尔大学）
