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The following results are related to COVID-19. Are you interested to view more results? Visit OpenAIRE - Explore.
11 Research products, page 1 of 2

  • COVID-19
  • Publications
  • Other research products
  • 2018-2022
  • Closed Access
  • English
  • COVID-19
  • Digital Humanities and Cultural Heritage

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  • Closed Access English
    Country: Netherlands

    From an Ancient Egyptian plague to the Black Death and Spanish flu, epidemics have often spurred societal transformations. Understanding why can help us create a better world after covid-19

  • Other research product . Other ORP type . 2022
    Closed Access English
    Authors: 
    Kelder, J.M.;
    Country: Netherlands

    From an Ancient Egyptian plague to the Black Death and Spanish flu, epidemics have often spurred societal transformations. Understanding why can help us create a better world after covid-19

  • Publication . Other literature type . Conference object . 2021
    Closed Access English
    Authors: 
    Karlo Babić; Milan Petrović; Slobodan Beliga; Sanda Martinčić-Ipšić; Marko Pranjic; Ana Meštrović;
    Country: Croatia

    In this paper, we explore the influence of COVID-19 related content in tweets on their spreadability. The experiment is performed in two steps on the dataset of tweets in the Croatian language posted during the COVID-19 pandemics. In the first step, we train a feedforward neural network model to predict if a tweet is highly-spreadable or not. The trained model achieves 62.5\% accuracy on the binary classification problem. In the second step, we use this model in a set of experiments for predicting the average spreadability of tweets. In these experiments, we separate the original dataset into two disjoint subsets: one composed of tweets filtered using COVID- 19 related keywords and the other that contains the rest of the tweets. Additionally, we modified these two subsets by adding and removing tokens into tweets and thus making them artificially COVID-19 related or not related. Our preliminary results indicate that tweets that are semantically related to COVID-19 have on average higher spreadability than the tweets that are not semantically related to COVID-19.

  • Publication . Other literature type . Part of book or chapter of book . 2021
    Closed Access English
    Authors: 
    Karlo Babić; Milan Petrović; Slobodan Beliga; Sanda Martinčić-Ipšić; Andrzej Jarynowski; Ana Meštrović;
    Country: Croatia

    In this paper, we analyze and compare Croatian and Polish Twitter datasets. After collecting tweets related to COVID-19 in the period from 20.01.2020 until 01.07.2020, we automatically annotated positive, negative, and neutral tweets with a simple method, and then used a classifier to annotate the dataset again. To interpret the data, the total number as well as the number of positive and negative tweets are plotted through time for Croatian and Polish tweets. The positive/negative fluctuations in the visualizations are explained in the context of certain events, such as the lockdowns, Easter, and parliamentary elections. In the last step, we analyze tokens by extracting the most frequently occurring tokens in positive or negative tweets and calculating the positive to negative (and reverse) ratios.

  • Closed Access English
    Authors: 
    Van Thuan Hoang; Ndiaw Goumballa; Jaffar A. Al-Tawfiq; Cheick Sokhna; Philippe Gautret;
    Publisher: HAL CCSD
    Country: France

    International audience

  • Closed Access English
    Authors: 
    Silvia Benvenuti; Daniele Gouthier;
    Publisher: Iated
    Country: Italy

    In winter 2020, the Covid-19 emergency explodes. From the earliest days, the Italian online magazine MaddMaths!, devoted to teaching and popularizing mathematics, decides to focus its attention on the mathematical aspects of the Sars-CoV-2 epidemic. The editorial choice is not to propose data and graphics but to publish articles for reflection, analysis, and dissemination on mathematical models as interpretative and political decision tools. Understanding the epidemic in order to combat it, is a scientific citizenship issue: citizens must have the tools to understand what is happening. In this article, we analyze how MaddMaths! and its readers interacted during the first year of Covid-19. We apply textual analysis methodologies and techniques to about ten articles per month that MaddMaths! has dedicated to an in-depth study of the mathematical aspects of Covid-19. And then we do a quantitative analysis to understand the interest they have found in the public. In contrast to the belief that the Internet is the place for fast and superficial communication, the existence of readers interested in deepening and understanding the mechanisms, including mathematical ones, of an epidemic, emerges. Although MaddMaths! does not usually cover health issues, its audience appreciated that the magazine has focused much of its work on communication. Communicating the mathematical models of a pandemic is a relevant form of health prevention. Understanding how Covid- 19 evolves means learning to manage the risks associated with the Sars-CoV-2 virus.

  • Closed Access English
    Authors: 
    Ilias Alami;
    Country: Netherlands

    This symposium brings together a range of Marxist perspectives on the state by both early career researchers and more established scholars I write this on day seven of a nation-wide police riot against anti-racist protests in the middle of a global pandemic during which the U S and U K states have failed to manage the outbreak of COVID-19, leading to the highest rate of unemployment since the Great Depression and tens of thousands of needless deaths And more is likely to unfold between now and publication These contributions were completed and submitted to Science & Society months ago Two of the contributions (Hunter and Munro) originally appeared in an earlier form in a series of blog posts "on the Marxist tradition of state dieory and its contemporary lineages," on die blog Legal Form, initiated by Chris O'Kane in 2019 So even diough the essays in this Symposium do not address recent events, diey nonetheless contain much that can help us understand the present situation This is powerful evidence of die enduring usefulness of Marxism and Marxist theories of the state

  • Publication . Other literature type . Part of book or chapter of book . 2021
    Closed Access English
    Authors: 
    Eleftherios Alexiou; Apostolos Antonakakis; Nemanja Jevtic; Georgios Sideras; Eftichia Farmaki; Sofronia Foutsitzi; Katia Lida Kermanidis;
    Publisher: HAL CCSD

    Since December 2019, Covid-19 has been spreading rapidly across the world. Unsurprisingly, conversation in social networks about Covid-19 is increasing as well. The aim of this study is to identify tentative Covid-19 infection cases through social networks and, specifically, on Twitter, using machine learning techniques. Tweets were collected using the data set “Covid-19 Twitter”, between November 1, 2020 and December 30, 2020, and manually marked by the authors of this study as positive (describing a tentative Covid-19 infection case) or negative (pertaining to any other Covid-19 related issue) cases of Covid-19, creating a smaller but more focused dataset. This study was conducted in three phases: a. data collection and data cleaning, b. processing and analysis of tweets by machine learning techniques, and c. evaluation and qualitative/quantitative analysis of the achieved results. The implementation was based on Gradient Boosting Decision Trees, Support Vector Machines (SVM) and Deep Learning algorithms.

  • Publication . Article . 2020
    Closed Access English
    Authors: 
    Connolly, M.; Phillips, A.; Shield, A.D.J.; Tongson, K.;
    Country: Netherlands

    The Velvet Light Trap gathered a diverse group of scholars with a range of specialties related to queer theory and media. This round-table touches on everything from dating apps to the films of John Waters to a livestreamed Indigo Girls concert, demonstrating the myriad ways digitality has affected queer media, representation, and audiences. The researchers began this discussion on 9 March 2020, only for closures due to the COVID-19 pandemic to begin in earnest a few days later. Thus, the participants' contributions began to reflect this fraught period toward the end of the conversation.

  • Other research product . Other ORP type . 2020
    Closed Access English
    Authors: 
    Rogers, James;
    Publisher: History Hit TV
    Country: Denmark

    In the past few months more than a billion people have faced restrictions unlike any seen before. Shops are closed; the death toll is rising; people across the globe have been forced to rise to an extraordinary challenge. But it is important to remember that humans have experienced pandemics before. In this documentary Dan Snow explores some of these previous pandemics and what they can teach us about Covid-19. He talks to Dr James Rogers about what lessons we can learn from WW2.

Advanced search in Research products
Research products
arrow_drop_down
Searching FieldsTerms
Any field
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includes
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Include:
The following results are related to COVID-19. Are you interested to view more results? Visit OpenAIRE - Explore.
11 Research products, page 1 of 2
  • Closed Access English
    Country: Netherlands

    From an Ancient Egyptian plague to the Black Death and Spanish flu, epidemics have often spurred societal transformations. Understanding why can help us create a better world after covid-19

  • Other research product . Other ORP type . 2022
    Closed Access English
    Authors: 
    Kelder, J.M.;
    Country: Netherlands

    From an Ancient Egyptian plague to the Black Death and Spanish flu, epidemics have often spurred societal transformations. Understanding why can help us create a better world after covid-19

  • Publication . Other literature type . Conference object . 2021
    Closed Access English
    Authors: 
    Karlo Babić; Milan Petrović; Slobodan Beliga; Sanda Martinčić-Ipšić; Marko Pranjic; Ana Meštrović;
    Country: Croatia

    In this paper, we explore the influence of COVID-19 related content in tweets on their spreadability. The experiment is performed in two steps on the dataset of tweets in the Croatian language posted during the COVID-19 pandemics. In the first step, we train a feedforward neural network model to predict if a tweet is highly-spreadable or not. The trained model achieves 62.5\% accuracy on the binary classification problem. In the second step, we use this model in a set of experiments for predicting the average spreadability of tweets. In these experiments, we separate the original dataset into two disjoint subsets: one composed of tweets filtered using COVID- 19 related keywords and the other that contains the rest of the tweets. Additionally, we modified these two subsets by adding and removing tokens into tweets and thus making them artificially COVID-19 related or not related. Our preliminary results indicate that tweets that are semantically related to COVID-19 have on average higher spreadability than the tweets that are not semantically related to COVID-19.

  • Publication . Other literature type . Part of book or chapter of book . 2021
    Closed Access English
    Authors: 
    Karlo Babić; Milan Petrović; Slobodan Beliga; Sanda Martinčić-Ipšić; Andrzej Jarynowski; Ana Meštrović;
    Country: Croatia

    In this paper, we analyze and compare Croatian and Polish Twitter datasets. After collecting tweets related to COVID-19 in the period from 20.01.2020 until 01.07.2020, we automatically annotated positive, negative, and neutral tweets with a simple method, and then used a classifier to annotate the dataset again. To interpret the data, the total number as well as the number of positive and negative tweets are plotted through time for Croatian and Polish tweets. The positive/negative fluctuations in the visualizations are explained in the context of certain events, such as the lockdowns, Easter, and parliamentary elections. In the last step, we analyze tokens by extracting the most frequently occurring tokens in positive or negative tweets and calculating the positive to negative (and reverse) ratios.

  • Closed Access English
    Authors: 
    Van Thuan Hoang; Ndiaw Goumballa; Jaffar A. Al-Tawfiq; Cheick Sokhna; Philippe Gautret;
    Publisher: HAL CCSD
    Country: France

    International audience

  • Closed Access English
    Authors: 
    Silvia Benvenuti; Daniele Gouthier;
    Publisher: Iated
    Country: Italy

    In winter 2020, the Covid-19 emergency explodes. From the earliest days, the Italian online magazine MaddMaths!, devoted to teaching and popularizing mathematics, decides to focus its attention on the mathematical aspects of the Sars-CoV-2 epidemic. The editorial choice is not to propose data and graphics but to publish articles for reflection, analysis, and dissemination on mathematical models as interpretative and political decision tools. Understanding the epidemic in order to combat it, is a scientific citizenship issue: citizens must have the tools to understand what is happening. In this article, we analyze how MaddMaths! and its readers interacted during the first year of Covid-19. We apply textual analysis methodologies and techniques to about ten articles per month that MaddMaths! has dedicated to an in-depth study of the mathematical aspects of Covid-19. And then we do a quantitative analysis to understand the interest they have found in the public. In contrast to the belief that the Internet is the place for fast and superficial communication, the existence of readers interested in deepening and understanding the mechanisms, including mathematical ones, of an epidemic, emerges. Although MaddMaths! does not usually cover health issues, its audience appreciated that the magazine has focused much of its work on communication. Communicating the mathematical models of a pandemic is a relevant form of health prevention. Understanding how Covid- 19 evolves means learning to manage the risks associated with the Sars-CoV-2 virus.

  • Closed Access English
    Authors: 
    Ilias Alami;
    Country: Netherlands

    This symposium brings together a range of Marxist perspectives on the state by both early career researchers and more established scholars I write this on day seven of a nation-wide police riot against anti-racist protests in the middle of a global pandemic during which the U S and U K states have failed to manage the outbreak of COVID-19, leading to the highest rate of unemployment since the Great Depression and tens of thousands of needless deaths And more is likely to unfold between now and publication These contributions were completed and submitted to Science & Society months ago Two of the contributions (Hunter and Munro) originally appeared in an earlier form in a series of blog posts "on the Marxist tradition of state dieory and its contemporary lineages," on die blog Legal Form, initiated by Chris O'Kane in 2019 So even diough the essays in this Symposium do not address recent events, diey nonetheless contain much that can help us understand the present situation This is powerful evidence of die enduring usefulness of Marxism and Marxist theories of the state

  • Publication . Other literature type . Part of book or chapter of book . 2021
    Closed Access English
    Authors: 
    Eleftherios Alexiou; Apostolos Antonakakis; Nemanja Jevtic; Georgios Sideras; Eftichia Farmaki; Sofronia Foutsitzi; Katia Lida Kermanidis;
    Publisher: HAL CCSD

    Since December 2019, Covid-19 has been spreading rapidly across the world. Unsurprisingly, conversation in social networks about Covid-19 is increasing as well. The aim of this study is to identify tentative Covid-19 infection cases through social networks and, specifically, on Twitter, using machine learning techniques. Tweets were collected using the data set “Covid-19 Twitter”, between November 1, 2020 and December 30, 2020, and manually marked by the authors of this study as positive (describing a tentative Covid-19 infection case) or negative (pertaining to any other Covid-19 related issue) cases of Covid-19, creating a smaller but more focused dataset. This study was conducted in three phases: a. data collection and data cleaning, b. processing and analysis of tweets by machine learning techniques, and c. evaluation and qualitative/quantitative analysis of the achieved results. The implementation was based on Gradient Boosting Decision Trees, Support Vector Machines (SVM) and Deep Learning algorithms.

  • Publication . Article . 2020
    Closed Access English
    Authors: 
    Connolly, M.; Phillips, A.; Shield, A.D.J.; Tongson, K.;
    Country: Netherlands

    The Velvet Light Trap gathered a diverse group of scholars with a range of specialties related to queer theory and media. This round-table touches on everything from dating apps to the films of John Waters to a livestreamed Indigo Girls concert, demonstrating the myriad ways digitality has affected queer media, representation, and audiences. The researchers began this discussion on 9 March 2020, only for closures due to the COVID-19 pandemic to begin in earnest a few days later. Thus, the participants' contributions began to reflect this fraught period toward the end of the conversation.

  • Other research product . Other ORP type . 2020
    Closed Access English
    Authors: 
    Rogers, James;
    Publisher: History Hit TV
    Country: Denmark

    In the past few months more than a billion people have faced restrictions unlike any seen before. Shops are closed; the death toll is rising; people across the globe have been forced to rise to an extraordinary challenge. But it is important to remember that humans have experienced pandemics before. In this documentary Dan Snow explores some of these previous pandemics and what they can teach us about Covid-19. He talks to Dr James Rogers about what lessons we can learn from WW2.