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8 results on '"Catanese, Elena"'

1. Integrating word embedding and topic modeling for sentiment analysis: A case study on the social mood on economy.

Author

Bruno, Mauro, Catanese, Elena, and De Cubellis, Massimo

Subjects
*NATURAL language processing, *RUSSIAN invasion of Ukraine, 2022-, *SENTIMENT analysis, *CONTENT analysis, *NONPROFIT sector
Abstract

In recent years, textual analysis and embedding spaces have become essential and complementary tools for sentiment analysis in National Statistics Institutes’ research, owing to their ability to summarize discussed topics effectively. Istat has developed an innovative tool, wordembox, which allows external users to explore the outputs of popular word embedding algorithms, such as Word2Vec and FastText. This tool enriches the analysis with a novel graph functionality, enabling users to discover clusters of words and facilitating implicit topic modeling. This article focuses on Social Mood on Economy (SME) posts over a period in which the index recorded a strong downward trend: the first month of the Russia-Ukraine conflict at the beginning of 2022. We compare findings from wordembox with standard topic modeling techniques, including Bayesian Latent Dirichlet Allocation (LDA), Top2Vec, and BERTopic, recent methods that extract clusters from word embedding spaces. These techniques show coherent results, and their combined use in textual analysis may create a synergy that enhances the informative content of synthetic indexes such as ‘Social Mood on Economy Index (SMEI)’. [ABSTRACT FROM AUTHOR]

Published
2024
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2. In the search for the low-complexity sequences in prokaryotic and eukaryotic genomes: how to derive a coherent picture from global and local entropy measures

Author

Acquisti, Claudia, Allegrini, Paolo, Bogani, Patrizia, Buiatti, Marcello, Catanese, Elena, Fronzoni, Leone, Grigolini, Paolo, Mersi, Giuseppe, and Palatella, Luigi

Subjects
Condensed Matter - Statistical Mechanics, Condensed Matter - Soft Condensed Matter, Quantitative Biology - Genomics
Abstract

We investigate on a possible way to connect the presence of Low-Complexity Sequences (LCS) in DNA genomes and the nonstationary properties of base correlations. Under the hypothesis that these variations signal a change in the DNA function, we use a new technique, called Non-Stationarity Entropic Index (NSEI) method, and we prove that this technique is an efficient way to detect functional changes with respect to a random baseline. The remarkable aspect is that NSEI does not imply any training data or fitting parameter, the only arbitrarity being the choice of a marker in the sequence. We make this choice on the basis of biological information about LCS distributions in genomes. We show that there exists a correlation between changing the amount in LCS and the ratio of long- to short-range correlation.

Published
2003
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7. Global Impact of the COVID-19 Pandemic on Stroke Volumes and Cerebrovascular Events

Author

Thanh N Nguyen, Muhammad M Qureshi, Piers Klein, Hiroshi Yamagami, Robert Mikulik, Anna Czlonkowska, Mohamad Abdalkader, Petra Sedova, Anvitha Sathya, Hannah C Lo, Mahmoud H Mohammaden, Diogo C Haussen, Espen Saxhaug Kristoffersen, Virginia Pujol Lereis, Sergio Daniel Scollo, Bruce CV Campbell, Alice Ma, James Orton Thomas, Mark W Parsons, Shaloo Singhal, Lee-Anne Slater, Rodrigo Tomazini Martins, Chris Enzinger, Thomas Gattringer, Aminur Rahman, Thomas Bonnet, Noemie Ligot, Sylvie De Raedt, Robin Lemmens, Peter Vanacker, Fenne Vandervorst, Adriana Bastos Conforto, Raquel CT Hidalgo, Luciana de Oliveira Neves, Rodrigo Targa Martins, Daissy Liliana Mora Cuervo, Leticia C Rebello, Igor Bessa Santiago, Isabelle Lameirinhas da Silva, Teodora Sakelarova, Rosen Kalpachki, Filip Alexiev, Luciana Catanese, Elena Adela Cora, Mayank Goyal, Michael D Hill, Michael E Kelly, Houman Khosravani, Pascale Lavoie, Lissa Peeling, Aleksandra Pikula, Rodrigo Rivera, Hui-Sheng Chen, Yimin Chen, Xiaochuan Huo, Zhongrong Miao, Shuiquan Yang, Marina Roje Bedekovic, Marina Bralic, Hrvoje Budincevic, Angel Basilio Corredor- Quintero, Osvaldo E Lara-Sarabia, Martin Cabal, Dusan Tenora, Petr Fibrich, Roman Herzig, Helena Hlaváčová, Emanuela Hrabanovska, David Hlinovsky, Lubomir Jurak, Raul G. Nogueira, and the SVIN COVID-19 Global Stroke Registry

Subjects
Stroke, IV thrombolysis, COVID-19 pandemic
Abstract

Declines in stroke admission, IV thrombolysis (IVT), and mechanical thrombectomy volumes were reported during the first wave of the COVID-19 pandemic. There is a paucity of data on the longer-term effect of the pandemic on stroke volumes over the course of a year and through the second wave of the pandemic. We sought to measure the effect of the COVID-19 pandemic on the volumes of stroke admissions, intracranial hemorrhage (ICH), IVT, and mechanical thrombectomy over a 1-year period at the onset of the pandemic (March 1, 2020, to February 28, 2021) compared with the immediately preceding year (March 1, 2019, to February 29, 2020).

Published
2022

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