ArAutoSenti: Automatic annotation and new tendencies for sentiment classification of Arabic messages

The file attached to this record is the author's final peer reviewed version.A corpus-based sentiment analysis approach for messages written in Arabic and its dialects is presented and implemented. The originality of this approach resides in the automation construction of the annotated sentiment corpus, which relies mainly on a sentiment lexicon that is also constructed automatically. For the classification step, shallow and deep classifiers are used with features being extracted applying word embedding models. For the validation of the constructed corpus, we proceed with a manual reviewing and it was found that 85.17% were correctly annotated. This approach is applied on the under-resourced Algerian dialect and the approach is tested on two external test corpora presented in the literature. The obtained results are very encouraging with an F1-score that is up to 88% (on the first test corpus) and up to 81% (on the second test corpus). These results respectively represent a 20% and a 6% improvement, respectively, when compared with existing work in the research literature

Metagenomic analysis of dental calculus in ancient Egyptian baboons

Dental calculus, or mineralized plaque, represents a record of ancient biomolecules and food residues. Recently, ancient metagenomics made it possible to unlock the wealth of microbial and dietary information of dental calculus to reconstruct oral microbiomes and lifestyle of humans from the past. Although most studies have so far focused on ancient humans, dental calculus is known to form in a wide range of animals, potentially informing on how human-animal interactions changed the animals' oral ecology. Here, we characterise the oral microbiome of six ancient Egyptian baboons held in captivity during the late Pharaonic era (9th-6th centuries BC) and of two historical baboons from a zoo via shotgun metagenomics. We demonstrate that these captive baboons possessed a distinctive oral microbiome when compared to ancient and modern humans, Neanderthals and a wild chimpanzee. These results may reflect the omnivorous dietary behaviour of baboons, even though health, food provisioning and other factors associated with human management, may have changed the baboons' oral microbiome. We anticipate our study to be a starting point for more extensive studies on ancient animal oral microbiomes to examine the extent to which domestication and human management in the past affected the diet, health and lifestyle of target animals

Edinburgh_UCL_Health@ SMM4H'22:From Glove to Flair for handling imbalanced healthcare corpora related to Adverse Drug Events, Change in medication and self-reporting vaccination

This paper reports on the performance of Edin-burgh_UCL_Health’s models in the Social Media Mining for Health (SMM4H) 2022 shared tasks. Our team participated in the tasks related to the Identification of Adverse Drug Events (ADEs), the classification of change in medication (change-med) and the classification of selfreport of vaccination (self-vaccine). Our best performing models are based on DeepADEM-iner (with respective F1= 0.64, 0.62 and 0.39 for ADE identification), on a GloVe model trained on Twitter (with F1=0.11 for the changemed) and finally on a stack embedding including a layer of Glove embedding and two layers of Flair embedding (with F1= 0.77 for selfreport)