Investigating the COVID-19 vaccine discussions on Twitter through a multilayer network-based approach
Modeling discussions on social networks is a challenging task, especially if we consider
sensitive topics, such as politics or healthcare. However, the knowledge hidden in these …
sensitive topics, such as politics or healthcare. However, the knowledge hidden in these …
Public health policy monitoring through public perceptions: a case of covid-19 tweet analysis
Since the start of the COVID-19 pandemic, government authorities have responded by
issuing new public health policies, many of which were intended to contain its spread but …
issuing new public health policies, many of which were intended to contain its spread but …
Emotion analysis using multilayered networks for graphical representation of tweets
Anticipating audience reaction towards a certain piece of text is integral to several facets of
society ranging from politics, research, and commercial industries. Sentiment analysis (SA) …
society ranging from politics, research, and commercial industries. Sentiment analysis (SA) …
HICL: Hashtag-Driven In-Context Learning for Social Media Natural Language Understanding
Natural language understanding (NLU) is integral to various social media applications.
However, the existing NLU models rely heavily on context for semantic learning, resulting in …
However, the existing NLU models rely heavily on context for semantic learning, resulting in …
A New Sentiment-Enhanced Word Embedding Method for Sentiment Analysis
Since some sentiment words have similar syntactic and semantic features in the corpus,
existing pre-trained word embeddings always perform poorly in sentiment analysis tasks …
existing pre-trained word embeddings always perform poorly in sentiment analysis tasks …
[HTML][HTML] Deconstructing cultural appropriation in online communities: A multilayer network analysis approach
E Corradini - Information Processing & Management, 2024 - Elsevier
In this study, we introduce a novel multilayer network model designed to analyze complex
social phenomena in online communities. The model captures intricate relationships …
social phenomena in online communities. The model captures intricate relationships …
Sentiment analysis of tweets using text and graph multi-views learning
LG Singh, SR Singh - Knowledge and Information Systems, 2024 - Springer
With the surge of deep learning framework, various studies have attempted to address the
challenges of sentiment analysis of tweets (data sparsity, under-specificity, noise, and …
challenges of sentiment analysis of tweets (data sparsity, under-specificity, noise, and …
Text classification problems via BERT embedding method and graph convolutional neural network
This paper presents a hybrid technique of combining the BERT embedding method and the
graph convolutional neural network. This combination is then employed to solve the text …
graph convolutional neural network. This combination is then employed to solve the text …
Characteristics of opinions in the societal and non-societal domains
LG Singh, SR Singh - Social Network Analysis and Mining, 2024 - Springer
With the increasing availability of user opinions on the web, understanding the distinct
nature of opinions in societal and non-societal contexts becomes crucial for opinion mining …
nature of opinions in societal and non-societal contexts becomes crucial for opinion mining …
Team error point at blp-2023 task 1: A comprehensive approach for violence inciting text detection using deep learning and traditional machine learning algorithm
In the modern digital landscape, social media platforms have the dual role of fostering
unprecedented connectivity and harboring a dark underbelly in the form of widespread …
unprecedented connectivity and harboring a dark underbelly in the form of widespread …