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Knowledge-Guided Sentiment Analysis via Learning From Natural Language Explanations

Zunwang Ke, Jiabao Sheng, Zhe Li, Wushour Silamu, Qinglang Guo
2021 IEEE Access  
analysis via deep learning.  ...  The annotation generated by natural language explanations is used as external knowledge to jointly train the sentiment analysis classifier.  ... 
doi:10.1109/access.2020.3048088 fatcat:z6cmaftlu5e4be2sndsvjbjnga

Analysis of Human Behavior by Mining Textual Data: Current Research Topics and Analytical Techniques

Edgar Gutierrez, Waldemar Karwowski, Krzysztof Fiok, Mohammad Reza Davahli, Tameika Liciaga, Tareq Ahram
2021 Symmetry  
[83] proposed a method for detecting suicide ideation by using sentiment analysis from tweets via supervised learning.  ...  Brand Sentiments in Customer Support Natural language processing Emotional [83] A Suicide Prediction System Based on Twitter Tweets Using Sentiment Analysis and Machine Learning Natural language  ... 
doi:10.3390/sym13071276 fatcat:hi5x22zfjfav3oorqm77rtaaaq

Reinforced Transformer with Cross-Lingual Distillation for Cross-Lingual Aspect Sentiment Classification

Hanqian Wu, Zhike Wang, Feng Qing, Shoushan Li
2021 Electronics  
language to the target language via Machine Translation (MT) tools.  ...  Though great progress has been made in the Aspect-Based Sentiment Analysis(ABSA) task through research, most of the previous work focuses on English-based ABSA problems, and there are few efforts on other  ...  source language classifier for guiding target language classifier to learn aspect-aware knowledge.  ... 
doi:10.3390/electronics10030270 fatcat:3el32uqfhbb45iktedchegzfem

Enjoy the Salience: Towards Better Transformer-based Faithful Explanations with Word Salience [article]

George Chrysostomou, Nikolaos Aletras
2021 arXiv   pre-print
Pretrained transformer-based models such as BERT have demonstrated state-of-the-art predictive performance when adapted into a range of natural language processing tasks.  ...  In this paper, we hypothesize that salient information extracted a priori from the training data can complement the task-specific information learned by the model during fine-tuning on a downstream task  ...  Acknowledgments NA is supported by EPSRC grant EP/V055712/1, part of the European Commission CHIST-ERA programme, call 2019 XAI: Explainable Machine Learning-based Artificial Intelligence.  ... 
arXiv:2108.13759v1 fatcat:k3ot3e2iijc45p6occplexg6gq

AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts [article]

Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, Eric Wallace, Sameer Singh
2020 arXiv   pre-print
Using AutoPrompt, we show that masked language models (MLMs) have an inherent capability to perform sentiment analysis and natural language inference without additional parameters or finetuning, sometimes  ...  The remarkable success of pretrained language models has motivated the study of what kinds of knowledge these models learn during pretraining.  ...  First, we use AUTO-PROMPT to construct prompts that test pretrained masked language models (MLMs) on sentiment analysis and natural language inference (NLI).  ... 
arXiv:2010.15980v2 fatcat:nnz2masus5ctnkm4pc477enrxi

Aspect Based Emotion Detection and Topic Modeling on Social Media Reviews [chapter]

Ganesh N. Jorvekar, Mohit Gangwar
2021 Advances in Parallel Computing  
Analysis of the emotions has drawn interest from researchers.  ...  In this Work we are trying to fill the gap between emotional recognition and emotional co-relation mining through social media reviews of natural language text.  ...  Implemented Expression Connection Processing on Natural Source Language Via Deep Learning Models, which undermines the connection of emotions depending on the success of speech signals from state-of-the-art  ... 
doi:10.3233/apc210242 fatcat:oh27gbrbp5ge3jspcaeyusmakq

Explainable Recommendation: A Survey and New Perspectives [article]

Yongfeng Zhang, Xu Chen
2020 arXiv   pre-print
The explanations may either be post-hoc or directly come from an explainable model (also called interpretable or transparent model in some contexts).  ...  We also devote a chapter to discuss the explanation perspectives in broader IR and AI/ML research.  ...  Researchers in the sentiment analysis community have explored both data mining and machine learning techniques for aspect-level sentiment analysis, which aims to extract aspect-sentiment pairs from text  ... 
arXiv:1804.11192v10 fatcat:scsd3htz65brbiae35zd3nixe4

Sentiment Analysis of Students' Feedback in MOOCs: A Systematic Literature Review

Fisnik Dalipi, Katerina Zdravkova, Fredrik Ahlgren
2021 Frontiers in Artificial Intelligence  
In recent years, sentiment analysis (SA) has gained popularity among researchers in various domains, including the education domain.  ...  To the best of our knowledge, this systematic review is the first of its kind.  ...  Furthermore, an analysis of sentiments of MOOC learners' posts via deep learning approach was conducted by (Li et al., 2019) .  ... 
doi:10.3389/frai.2021.728708 pmid:34568815 pmcid:PMC8459797 fatcat:is7patb7mvcrrn3ryd2kjebxom

Explaining Arguments with Background Knowledge

Maria Becker, Ioana Hulpuş, Juri Opitz, Debjit Paul, Jonathan Kobbe, Heiner Stuckenschmidt, Anette Frank
2020 Datenbank-Spektrum  
We introduce the problems and challenges we need to address, and present the progress we achieved until now by applying advanced natural language and knowledge processing methods.  ...  News -often from questionable sources -are spread online, as are election campaigns; calls for (collective) action spread with unforeseen speed and intensity.  ...  Learning from Human-Generated Data In a recent annotation project [2, 4] on argumentative texts, we elicitated high-quality human annotations of implied information in the form of simple natural language  ... 
doi:10.1007/s13222-020-00348-6 fatcat:zd55bxjr7bhs5ab5whi3ih4q4y

Analyzing TripAdvisor reviews of wine tours: an approach based on text mining and sentiment analysis

Elena Barbierato, Iacopo Bernetti, Irene Capecchi
2021 International Journal of Wine Business Research  
Design/methodology/approach The study combines approaches of text mining, sentiment analysis and natural language processing, drawing on data from the TripAdvisor platform, obtaining through an automatic  ...  natural language processing approaches.  ...  The results obtained from the analysis of natural language processing are confirmed by the five sentences with the highest sentiment scores shown in Table 2 .  ... 
doi:10.1108/ijwbr-04-2021-0025 fatcat:ta6iq6jdvbecxkmo2ltg5ttgz4

Learning from Explanations with Neural Execution Tree [article]

Ziqi Wang, Yujia Qin, Wenxuan Zhou, Jun Yan, Qinyuan Ye, Leonardo Neves, Zhiyuan Liu, Xiang Ren
2020 arXiv   pre-print
Natural language (NL) explanations have been demonstrated very useful additional supervision, which can provide sufficient domain knowledge for generating more labeled data over new instances, while the  ...  Experiments on two NLP tasks (relation extraction and sentiment analysis) demonstrate its superiority over baseline methods.  ...  ACKNOWLEDGMENTS This research is based upon work supported in part by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via Contract  ... 
arXiv:1911.01352v3 fatcat:fqbntowaj5addj4h3o6fasbykm

National Leaders' Usage of Twitter in Response to COVID-19: A Sentiment Analysis

Yuming Wang, Stephen M Croucher, Erika Pearson
2021 Frontiers in Communication  
We used natural language processing (NLP) and conducted sentiment analysis via Python to identify frames and to compare the leaders' messaging.  ...  2) Which frames emerged from tweet content of each leader regarding COVID-19? 3) What was the overall tweet valence of each leader regarding COVID-19?  ...  Follow-up research could retrain the sentiment analysis model learning from the current analysis.  ... 
doi:10.3389/fcomm.2021.732399 fatcat:fw3tgxylaba7rbzsjevbrxp3bu

Local Interpretations for Explainable Natural Language Processing: A Survey [article]

Siwen Luo and Hamish Ivison and Caren Han and Josiah Poon
2021 arXiv   pre-print
This work investigates various methods to improve the interpretability of deep neural networks for natural language processing (NLP) tasks, including machine translation and sentiment analysis.  ...  language explanation; 3) probing the hidden states of models and word representations.  ...  Natural Language Explanation Natural language explanation (NLE) refers to the method of generating text explanations for a model's predictions.  ... 
arXiv:2103.11072v1 fatcat:7453vleiqfd73fde7gp3222mtm

Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey [article]

Bonan Min, Hayley Ross, Elior Sulem, Amir Pouran Ben Veyseh, Thien Huu Nguyen, Oscar Sainz, Eneko Agirre, Ilana Heinz, Dan Roth
2021 arXiv   pre-print
Large, pre-trained transformer-based language models such as BERT have drastically changed the Natural Language Processing (NLP) field.  ...  We present a survey of recent work that uses these large language models to solve NLP tasks via pre-training then fine-tuning, prompting, or text generation approaches.  ...  , and sentiment analysis.  ... 
arXiv:2111.01243v1 fatcat:4xfjkkby2bfnhdrhmrdlliy76m

Hierarchical Interaction Networks with Rethinking Mechanism for Document-level Sentiment Analysis [article]

Lingwei Wei, Dou Hu, Wei Zhou, Xuehai Tang, Xiaodan Zhang, Xin Wang, Jizhong Han, Songlin Hu
2021 arXiv   pre-print
Document-level Sentiment Analysis (DSA) is more challenging due to vague semantic links and complicate sentiment information.  ...  Furthermore, we design a Sentiment-based Rethinking mechanism (SR) by refining the HIN with sentiment label information to learn a more sentiment-aware document representation.  ...  Bhargava and Sharma [22] leveraged different techniques of machine learning to perform sentiment analysis of different languages.  ... 
arXiv:2007.08445v3 fatcat:vambia2wnfexrkmchdihyqh4ka
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