[HTML][HTML] A review on sentiment analysis from social media platforms
M Rodríguez-Ibánez, A Casánez-Ventura… - Expert Systems with …, 2023 - Elsevier
Sentiment analysis has proven to be a valuable tool to gauge public opinion in different
disciplines. It has been successfully employed in financial market prediction, health issues …
disciplines. It has been successfully employed in financial market prediction, health issues …
COVID-19 sensing: negative sentiment analysis on social media in China via BERT model
Coronavirus disease 2019 (COVID-19) poses massive challenges for the world. Public
sentiment analysis during the outbreak provides insightful information in making appropriate …
sentiment analysis during the outbreak provides insightful information in making appropriate …
ASQA: Factoid questions meet long-form answers
An abundance of datasets and availability of reliable evaluation metrics have resulted in
strong progress in factoid question answering (QA). This progress, however, does not easily …
strong progress in factoid question answering (QA). This progress, however, does not easily …
Humanized recommender systems: State-of-the-art and research issues
Psychological factors such as personality, emotions, social connections, and decision
biases can significantly affect the outcome of a decision process. These factors are also …
biases can significantly affect the outcome of a decision process. These factors are also …
Comparison of deep learning models and various text pre-processing techniques for the toxic comments classification
The emergence of anti-social behaviour in online environments presents a serious issue in
today's society. Automatic detection and identification of such behaviour are becoming …
today's society. Automatic detection and identification of such behaviour are becoming …
Detecting errors and estimating accuracy on unlabeled data with self-training ensembles
When a deep learning model is deployed in the wild, it can encounter test data drawn from
distributions different from the training data distribution and suffer drop in performance. For …
distributions different from the training data distribution and suffer drop in performance. For …
Learning program semantics with code representations: An empirical study
Program semantics learning is the core and fundamental for various code intelligent tasks
eg, vulnerability detection, clone detection. A considerable amount of existing works …
eg, vulnerability detection, clone detection. A considerable amount of existing works …
Tiara: deep learning-based classification system for eukaryotic sequences
Motivation With a large number of metagenomic datasets becoming available, eukaryotic
metagenomics emerged as a new challenge. The proper classification of eukaryotic nuclear …
metagenomics emerged as a new challenge. The proper classification of eukaryotic nuclear …
Subjective answers evaluation using machine learning and natural language processing
MF Bashir, H Arshad, AR Javed, N Kryvinska… - IEEE …, 2021 - ieeexplore.ieee.org
Subjective paper evaluation is a tricky and tiresome task to do by manual labor. Insufficient
understanding and acceptance of data are crucial challenges while analyzing subjective …
understanding and acceptance of data are crucial challenges while analyzing subjective …
Attention-based LSTM network for rumor veracity estimation of tweets
Twitter has become a fertile place for rumors, as information can spread to a large number of
people immediately. Rumors can mislead public opinion, weaken social order, decrease the …
people immediately. Rumors can mislead public opinion, weaken social order, decrease the …