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Found 5 papers, 0 papers with code
A Late Fusion Framework with Multiple Optimization Methods for Media Interestingness
The extraction of such meaningful information is a complex task and generally, the performance of individual algorithms is very low.
Sentiment Analysis of Users' Reviews on COVID-19 Contact Tracing Apps with a Benchmark Dataset
In this work, we propose a pipeline starting from manual annotation via a crowd-sourcing study and concluding on the development and training of AI models for automatic sentiment analysis of users' reviews.
Floods Detection in Twitter Text and Images
The extracted features are then used to train multiple individual classifiers whose scores are then combined in a late fusion manner achieving an F1-score of 0. 75%.
Fake News Detection in Social Media using Graph Neural Networks and NLP Techniques: A COVID-19 Use-case
On the binary classification, the BoW and BERT based solutions obtained an average F1-score of . 666% and . 693%, respectively.
Active Learning for Event Detection in Support of Disaster Analysis Applications
Disaster analysis in social media content is one of the interesting research domains having abundance of data.
