Impact of word embedding models on text analytics in deep learning environment: a review
The selection of word embedding and deep learning models for better outcomes is vital.
Word embeddings are an n-dimensional distributed representation of a text that attempts to …
Word embeddings are an n-dimensional distributed representation of a text that attempts to …
[HTML][HTML] A survey on hate speech detection and sentiment analysis using machine learning and deep learning models
In today's digital era, the rise of hate speech has emerged as a critical concern, driven by the
rapid information-sharing capabilities of social media platforms and online communities. As …
rapid information-sharing capabilities of social media platforms and online communities. As …
[HTML][HTML] Detecting abusive comments at a fine-grained level in a low-resource language
YouTube is a video-sharing and social media platform where users create profiles and
share videos for their followers to view, like, and comment on. Abusive comments on videos …
share videos for their followers to view, like, and comment on. Abusive comments on videos …
Novel hate speech detection using word cloud visualization and ensemble learning coupled with count vectorizer
T Turki, SS Roy - Applied Sciences, 2022 - mdpi.com
A plethora of negative behavioural activities have recently been found in social media.
Incidents such as trolling and hate speech on social media, especially on Twitter, have …
Incidents such as trolling and hate speech on social media, especially on Twitter, have …
Enhancing social network hate detection using back translation and GPT-3 augmentations during training and test-time
Social media platforms have become an essential means of communication, but they also
serve as a breeding ground for hateful content. Detecting hate speech accurately is …
serve as a breeding ground for hateful content. Detecting hate speech accurately is …
ROUGE-SEM: Better evaluation of summarization using ROUGE combined with semantics
M Zhang, C Li, M Wan, X Zhang, Q Zhao - Expert Systems with Applications, 2024 - Elsevier
With the development of pre-trained language models and large-scale datasets, automatic
text summarization has attracted much attention from the community of natural language …
text summarization has attracted much attention from the community of natural language …
Online offensive behaviour in socialmedia: Detection approaches, comprehensive review and future directions
The enormous growth of social media provides a platform for displaying harmful, offensive
online behaviour, which keeps increasing with time. The popularity of smartphones and the …
online behaviour, which keeps increasing with time. The popularity of smartphones and the …
[HTML][HTML] Fine-tuned sentiment analysis of COVID-19 vaccine–related social media data: comparative study
Background The emergence of the novel coronavirus (COVID-19) and the necessary
separation of populations have led to an unprecedented number of new social media users …
separation of populations have led to an unprecedented number of new social media users …
Question classification using limited labelled data
C Mallikarjuna, S Sivanesan - Information Processing & Management, 2022 - Elsevier
Question classification (QC) involves classifying given question based on the expected
answer type and is an important task in the Question Answering (QA) system. Existing …
answer type and is an important task in the Question Answering (QA) system. Existing …
RETRACTED ARTICLE: Multilingual hate speech detection sentimental analysis on social media platforms using optimal feature extraction and hybrid diagonal gated …
P Kar, S Debbarma - The Journal of Supercomputing, 2023 - Springer
Many activities are conducted on social media platforms, such as promoting products,
sharing news and sharing achievements. As a result of users' freedom and anonymity on …
sharing news and sharing achievements. As a result of users' freedom and anonymity on …