Sentiment analysis of public social media as a tool for health-related topics
For decades, researchers have experimented with the possibility that machines can equal
human linguistic capabilities. Recently, advances in the field of natural language processing …
human linguistic capabilities. Recently, advances in the field of natural language processing …
Sentiment analysis for covid-19 tweets using recurrent neural network (rnn) and bidirectional encoder representations (bert) models
In the last few decades, social media usage has exponentially increased, and people often
share information covering various topics of interest. The social media platforms such as …
share information covering various topics of interest. The social media platforms such as …
Unsupervised genre-based multidomain sentiment lexicon learning using corpus-generated polarity seed words
Sentiment lexicon learning is of paramount importance in sentiment analysis. One of the
most considerable challenges in learning sentiment lexicons is their domain-specific …
most considerable challenges in learning sentiment lexicons is their domain-specific …
A trustworthiness-aware spatial task allocation using a fuzzy-based trust and reputation system approach
MM Rahman, NA Abdullah - Expert Systems with Applications, 2023 - Elsevier
Abstract Unlike crowdsourcing, Spatial Crowdsourcing (SC) requires workers to travel to a
specific physical location to accomplish a task. Due to its open concept, the platform accepts …
specific physical location to accomplish a task. Due to its open concept, the platform accepts …
Extending a fuzzy polarity propagation method for multi-domain sentiment analysis with word embedding and pos tagging
Within multi-domain sentiment analysis, we study how different domain-dependent polarities
can be learned for the same concepts. To this aim, we extend an existing approach based …
can be learned for the same concepts. To this aim, we extend an existing approach based …
Deterministic solution of algebraic equations in sentiment analysis
Text mining methods usually use statistical information to solve text and language-
independent procedures. Text mining methods such as polarity detection based on …
independent procedures. Text mining methods such as polarity detection based on …
Enhancing cross-domain sentiment classification through multi-source collaborative training and selective ensemble methods
C Zhao, X Yang, X Sun, L Shen, J Gao… - The Journal of …, 2024 - Springer
Due to the varying data distributions in different domains, transferring sentiment
classification models across domains is often infeasible. Additionally, labeling data in …
classification models across domains is often infeasible. Additionally, labeling data in …
Empirical Study and Mitigation Methods of Bias in LLM-Based Robots
R Zhou - Academic Journal of Science and Technology, 2024 - drpress.org
Our study provides a comprehensive analysis of biased behaviors exhibited by robots
utilizing large language models (LLMs) in real-world applications, focusing on five …
utilizing large language models (LLMs) in real-world applications, focusing on five …
Improving the Cross-Domain Classification of Short Text Using the Deep Transfer Learning Framework
A Monemi Rad, N Abdolvand… - Journal of Information …, 2024 - jitm.ut.ac.ir
With the advent of user-generated text information on the Internet, text sentiment analysis
plays an essential role in online business transactions. The expression of feelings and …
plays an essential role in online business transactions. The expression of feelings and …
Sentiment analysis a deep survey on methods and approaches
R Bhati - 2020 - 210.212.169.38
In this paper we present an in-depth analysis of sentiment. It also offers a survey and
discusses the latest papers and techniques relevant to strategies for lexicon-based …
discusses the latest papers and techniques relevant to strategies for lexicon-based …