Online Learning Communities in COVID-19 Days: Mining Twitter Data

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  • Author(s): Bozkurt, Mahmut (ORCID Bozkurt, Mahmut (ORCID 0000-0002-3169-6819)
  • Language:
    English
  • Source:
    International Technology and Education Journal. Dec 2021 5(2):67-74.
  • Publication Date:
    2021
  • Document Type:
    Journal Articles
    Reports - Research
  • Additional Information
    • Availability:
      International Technology and Education Journal. Available from: Sayim Aktay, Mugla Sitki Kocman University, Educational Faculty, Mentese, Mugla 48000, Turkey. Tel: +90 252 211 22 25; e-mail: [email protected]; Web site: http://itejournal.com/
    • Peer Reviewed:
      Y
    • Source:
      8
    • Subject Terms:
      COVID-19; Pandemics; Online Courses; Communities of Practice; Networks; Social Media; Telecommunications; Educational Technology; Information Retrieval; Web Sites; Vocabulary; Teachers
    • ISSN:
      2602-2885
    • Abstract:
      As a teacher educator who provides online education during the pandemic process, I wanted to examine what is needed and what is shared in online learning communities. The aim of this research is to reveal the most shared concepts and sentiments in online learning networks using the data obtained from Twitter. In this context, the #edtech hashtag, one of the most shared hashtags, was chosen and a total of 134,101 unique tweets were analyzed in the specified time period with some data mining and sentiment analysis techniques. As a result of these analyzes, the most shared websites, words and bigrams were extracted. In addition, sentiment analysis based on NRC and Bing lexicons was also performed. According to the findings about the most shared websites, it has been seen that, in addition to current learning approaches such as digital learning designs, STEAM, coding, robotics, artificial intelligence and augmented reality, various mathematical calculation applications and websites based on fun math activities are shared. The words learning, student, school, education, online, free, classroom, teacher, join and check are the most used words. The most used bigrams are activity pack, remote learning, pupil activity, online learning and google classroom. Considering the sentiment analysis, it was seen that the most prominent sentiment based on the NRC lexicon was positive, followed by the sentiments of trust, anticipation and joy. According to Bing, positive sentiments were dominant.
    • Abstract:
      As Provided
    • Publication Date:
      2022
    • Accession Number:
      EJ1338068