In this exploratory study, we scrutinize a database of over one million tweets collected from
March to July 2020 to illustrate public attitudes towards mask usage during the COVID-19 …

This paper presents profile and social network analyses on concise systematic review
corpora. It suggests two new robots and platforms for profile and social network analyses …

Users are often overwhelmed by the amount of information generated on online social
networks and media (OSNEM), in particular Twitter, during particular events. Summarizing …

Obtaining meaning-rich representations of social media inputs, such as Tweets
(unstructured and noisy text), from general-purpose pre-trained language models has …

In this paper, a new theory to train neural networks is presented which is called “Neural
Network Meaningful Learning”(NNMeL) theory. According to this theory, meaningful learning …

NLP pipelines with limited or no labeled data, rely on unsupervised methods for document
processing. Unsupervised approaches typically depend on clustering of terms or …

Despite recent Artificial Intelligence (AI) advances in narrow task areas such as face
recognition and natural language processing, the emergence of general machine …

To unfold the tremendous amount of multimedia data uploaded daily to social media
platforms, effective topic modeling techniques are needed. Existing work tends to apply topic …

Many debt collection companies need to rely on research focusing on data analysis
methods that can assist them to analyse their unstructured data which holds information that …

The task of automatically analyzing the textual content of documents faces a number of
challenges in general but even more so when dealing with the medical domain. Here, we …