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Global monitoring of school closure caused by COVID‐19 (UNESCO, 2020a) [Colour figure can be viewed at wileyonlinelibrary.com]

Global monitoring of school closure caused by COVID‐19 (UNESCO, 2020a) [Colour figure can be viewed at wileyonlinelibrary.com]

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The current educational disruption caused by the COVID‐19 pandemic has fuelled a plethora of investments and the use of educational technologies for Emergency Remote Learning (ERL). Despite the significance of online learning for ERL across most educational institutions, there are wide mixed perceptions about online learning during this pandemic. T...

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... El uso de estrategias didácticas tradicionales y emergentes incluyó la adaptación de estrategias educativas según el lugar y el momento de la pandemia, se utilizaron medios de comunicación, plataformas, guías de trabajo, imágenes y redes sociales (Asare et al., 2021;O'Keeffe & McNally, 2021, 2022Videla et al., 2022). Van Cappelle et al. (2021) y Damani et al. (2022) resaltan el proceso de adaptación de la tecnología educativa (EdTech) a las necesidades durante la pandemia, que dio lugar a enfoques no-tech, low-tech y high-tech de acuerdo a los contextos y recursos locales. ...
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... Ref. [50] explored the potential of multimedia tweets in communicating emerging health information. According to [51], Twitter (X) has served as a crucial data source for academics and business experts conducting social media research since it was launched. When the COVID-19 outbreak began, Twitter (X) developed into a vital resource for all populations to gather and exchange information, form opinions, and express insights about COVID-19 [52]. ...
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This paper presents several novel findings from a comprehensive analysis of about 50,000 Tweets about online learning during COVID-19, posted on Twitter between 9 November 2021 and 13 July 2022. First, the results of sentiment analysis from VADER, Afinn, and TextBlob show that a higher percentage of these Tweets were positive. The results of gender-specific sentiment analysis indicate that for positive Tweets, negative Tweets, and neutral Tweets, between males and females, males posted a higher percentage of the Tweets. Second, the results from subjectivity analysis show that the percentage of least opinionated, neutral opinionated, and highly opinionated Tweets were 56.568%, 30.898%, and 12.534%, respectively. The gender-specific results for subjectivity analysis indicate that females posted a higher percentage of highly opinionated Tweets as compared to males. However, males posted a higher percentage of least opinionated and neutral opinionated Tweets as compared to females. Third, toxicity detection was performed on the Tweets to detect different categories of toxic content—toxicity, obscene, identity attack, insult, threat, and sexually explicit. The gender-specific analysis of the percentage of Tweets posted by each gender for each of these categories of toxic content revealed several novel insights related to the degree, type, variations, and trends of toxic content posted by males and females related to online learning. Fourth, the average activity of males and females per month in this context was calculated. The findings indicate that the average activity of females was higher in all months as compared to males other than March 2022. Finally, country-specific tweeting patterns of males and females were also performed which presented multiple novel insights, for instance, in India, a higher percentage of the Tweets about online learning during COVID-19 were posted by males as compared to females.
... The results indicated positive sentiment from elementary through high school, but negative sentiment for universities. The work by Asare et al. [95] aimed to cluster the most commonly used words into general topics or themes. The analysis of different topics found 48.9% of positive tweets, with "learning," "COVID," "online," and "distance" being the most used words. ...
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The work presented in this paper presents several novel findings from a comprehensive analysis of about 50,000 Tweets about online learning during COVID-19, posted on Twitter between November 9, 2021, and July 13, 2022. First, the results of sentiment analysis from VADER, Afinn, and TextBlob show that a higher percentage of these tweets were positive. The results of gender-specific sentiment analysis indicate that for positive tweets, negative tweets, and neutral tweets, between males and females, males posted a higher percentage of the tweets. Second, the results from subjectivity analysis show that the percentage of least opinionated, neutral opinionated, and highly opinionated tweets were 56.568%, 30.898%, and 12.534%, respectively. The gender-specific results for subjectivity analysis indicate that for each subjectivity class, males posted a higher percentage of tweets as compared to females. Third, toxicity detection was performed on the tweets to detect different categories of toxic content - toxicity, obscene, identity attack, insult, threat, and sexually explicit. The gender-specific analysis of the percentage of tweets posted by each gender in each of these categories revealed several novel insights. For instance, for the sexually explicit category, females posted a higher percentage of tweets as compared to males. Fourth, gender-specific tweeting patterns for each of these categories of toxic content were analyzed to understand the trends of the same. The results unraveled multiple paradigms of tweeting behavior, for instance, the intensity of obscene content in tweets about online learning by males and females has decreased since May 2022. Fifth, the average activity of males and females per month was calculated. The findings indicate that the average activity of females has been higher in all months as compared to males other than March 2022. Finally, country-specific tweeting patterns of males and females were also performed which presented multiple novel insights, for instance, in India a higher percentage of the tweets about online learning during COVID-19 were posted by males as compared to females.