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Knowledge-Guided Sentiment Analysis via Learning From Natural Language Explanations
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
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
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]
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]
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]
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]
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
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
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
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]
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
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]
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]
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]
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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