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Social Media Toxicity Classification Using Deep Learning: Real-World Application UK Brexit

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Twitter power: Tweets as electronic word of mouth
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Analysis of Tweets in Arabic Language for Detection of Road Traffic Conditions
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Survey on Sentiment Analysis Methods for Reputation Evaluation
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Survey on Sentiment Analysis from Affective Multimodal Content
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Predicting Election Result with Sentimental Analysis Using Twitter Data for Candidate Selection
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Multimedia summarization using social media content
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A survey on sentiment analysis and opinion mining for social multimedia
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Sentiment analysis in teaching evaluations using sentiment phrase pattern matching (SPPM) based on association mining
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Consumer insight mining: Aspect based Twitter opinion mining of mobile phone reviews
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Effects of anonymity, invisibility, and lack of eye-contact on toxic online disinhibition
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Perpetuating online sexism offline: Anonymity, interactivity, and the effects of sexist hashtags on social media
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Aquila Optimizer: A novel meta-heuristic optimization algorithm
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The Arithmetic Optimization Algorithm
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Deep contextualized embeddings for quantifying the informative content in biomedical text summarization
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Extracting comprehensive clinical information for breast cancer using deep learning methods
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A study of entity-linking methods for normalizing Chinese diagnosis and procedure terms to ICD codes
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News impact on stock price return via sentiment analysis
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Carrying out consensual Group Decision Making processes under social networks using sentiment analysis over comparative expressions
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Multi-source data fusion for aspect-level sentiment classification
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Politics, sentiments, and misinformation: An analysis of the Twitter discussion on the 2016 Austrian Presidential Elections
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Measuring semantic similarity of clinical trial outcomes using deep pre-trained language representations
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Happiness and the Patterns of Life: A Study of Geolocated Tweets
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Cyberbullying Via Social Media
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Domestic Violence Crisis Identification From Facebook Posts Based on Deep Learning
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Sentiment Identification in Football-Specific Tweets
inferredcites →https://doi.org/10.1109/access.2019.2908827openalex-snapshot
Deep Learning for Multi-Class Identification From Domestic Violence Online Posts
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Target-Dependent Sentiment Classification With BERT
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Deep Entity Linking via Eliminating Semantic Ambiguity With BERT
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Twitter sentiment analysis of online transportation service providers
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Convolutional MKL Based Multimodal Emotion Recognition and Sentiment Analysis
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Overlapping Toxic Sentiment Classification Using Deep Neural Architectures
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Imbalanced Toxic Comments Classification Using Data Augmentation and Deep Learning
inferredcites →https://doi.org/10.1109/icsc.2016.20openalex-snapshot
Multimedia Social Network Modeling: A Proposal
inferredcites →https://doi.org/10.1109/iucc/dsci/smartcns.2019.00030openalex-snapshot
Real-Time Traffic Congestion Analysis Based on Collected Tweets
inferredcites →https://doi.org/10.1109/mis.2013.34openalex-snapshot
YouTube Movie Reviews: Sentiment Analysis in an Audio-Visual Context
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Sentiment analysis of Twitter data for predicting stock market movements
inferredcites →https://doi.org/10.1109/tgrs.2019.2934760openalex-snapshot
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Sentiment analysis of tweets for the 2016 US presidential election
inferredcites →https://doi.org/10.1145/2542182.2542190openalex-snapshot
Forecasting with twitter data
inferredcites →https://doi.org/10.1145/2702123.2702529openalex-snapshot
Exploring Cyberbullying and Other Toxic Behavior in Team Competition Online Games
inferredcites →https://doi.org/10.1145/2938640openalex-snapshot
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inferredcites →https://doi.org/10.1145/3038912.3052591openalex-snapshot
Ex Machina
inferredcites →https://doi.org/10.1145/3200947.3208069openalex-snapshot
Convolutional Neural Networks for Toxic Comment Classification
inferredcites →https://doi.org/10.1145/3406865.3418329openalex-snapshot
IPOD: A Large-scale Industrial and Professional Occupation Dataset
inferredcites →https://doi.org/10.1162/tacl_a_00349openalex-snapshot
A Primer in BERTology: What We Know About How BERT Works
inferredcites →https://doi.org/10.1177/0047287517747753openalex-snapshot
Sentiment Analysis in Tourism: Capitalizing on Big Data
inferredcites →https://doi.org/10.1186/s13673-018-0147-4openalex-snapshot
Personality classification based on profiles of social networks’ users and the five-factor model of personality
inferredcites →https://doi.org/10.1186/s13673-019-0185-6openalex-snapshot
Detection and classification of social media-based extremist affiliations using sentiment analysis techniques
inferredcites →https://doi.org/10.1186/s40537-018-0164-1openalex-snapshot
Prediction and analysis of Indonesia Presidential election from Twitter using sentiment analysis
inferredcites →https://doi.org/10.1186/s40537-019-0195-2openalex-snapshot
Arabia Felix 2.0: a cross-linguistic Twitter analysis of happiness patterns in the United Arab Emirates
inferredcites →https://doi.org/10.1186/s40537-019-0208-1openalex-snapshot
Oscillation of tweet sentiments in the election of João Doria Jr. for Mayor
inferredcites →https://doi.org/10.1542/peds.2011-0054openalex-snapshot
The Impact of Social Media on Children, Adolescents, and Families
inferredcites →https://doi.org/10.1542/peds.2016-1758eopenalex-snapshot
Benefits and Costs of Social Media in Adolescence
inferredcites →https://doi.org/10.1609/aaai.v29i1.9179openalex-snapshot
Robust Image Sentiment Analysis Using Progressively Trained and Domain Transferred Deep Networks
inferredcites →https://doi.org/10.18653/v1/w19-5058openalex-snapshot
NCUEE at MEDIQA 2019: Medical Text Inference Using Ensemble BERT-BiLSTM-Attention Model
inferredcites →https://doi.org/10.3390/a13120345openalex-snapshot
Nature-Inspired Optimization Algorithms for Text Document Clustering—A Comprehensive Analysis
inferredcites →https://doi.org/10.3390/electronics10020101openalex-snapshot
Advances in Meta-Heuristic Optimization Algorithms in Big Data Text Clustering
inferredcites →https://doi.org/10.3390/su11195201openalex-snapshot
The Truth behind the Brexit Vote: Clearing away Illusion after Two Years of Confusion
inferredcites →https://doi.org/10.4230/tgdk.3.3.5openalex-snapshot
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
inferredcites →https://doi.org/10.48550/arxiv.1906.08237openalex-snapshot
XLNet: Generalized Autoregressive Pretraining for Language Understanding
inferredcites →https://doi.org/10.48550/arxiv.1909.08053openalex-snapshot
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism
inferredcites →https://doi.org/10.48550/arxiv.1910.10495openalex-snapshot
IPOD: An Industrial and Professional Occupations Dataset and its Applications to Occupational Data Mining and Analysis
inferredcites →https://doi.org/10.48550/arxiv.2005.14165openalex-snapshot
Language Models are Few-Shot Learners

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