3 Matching Annotations
  1. Aug 2021
  2. psyarxiv.com psyarxiv.com
    How Japanese citizens faced the COVID-19 pandemic?: Exploration from twitter
    1
    1. lucyparfitt16 11 Aug 2021

      Saire, Josimar. E. Chire., & Masuyama, A. (2021). How Japanese citizens faced the COVID-19 pandemic?: Exploration from twitter [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/64x7s

      is:preprint lang:en Japan COVID-19 Twitter text mining twitter analytics Google trends social media Google research psychology behavioral science information
    Visit annotations in context

    Tags

    Annotators

    URL

    psyarxiv.com/64x7s/
  3. May 2020
  4. psyarxiv.com psyarxiv.com
    Modeling latent topics in social media using Dynamic Exploratory Graph Analysis: The case of the right-wing and left-wing trolls in the 2016 US elections
    1
    1. edampf 29 May 2020

      Golino, H., Christensen, A. P., Moulder, R. G., Kim, S., & Boker, S. M. (2020, April 14). Modeling latent topics in social media using Dynamic Exploratory Graph Analysis: The case of the right-wing and left-wing trolls in the 2016 US elections. https://doi.org/10.31234/osf.io/tfs7c

      is:preprint lang:en dynamics latent topic analysis network model text mining time embedding social media troll USA election 2016 right-wing left-wing simulation modeling Russia Twitter research
    Visit annotations in context

    Tags

    Annotators

    URL

    psyarxiv.com/tfs7c/
  5. www.annualreviews.org www.annualreviews.org
    Mining Social Media Data for Biomedical Signals and Health-Related Behavior
    1
    1. Gaurav_Saxena 25 May 2020

      Correia, Rion Brattig, Ian B. Wood, Johan Bollen, and Luis M. Rocha. “Mining Social Media Data for Biomedical Signals and Health-Related Behavior.” Annual Review of Biomedical Data Science, May 4, 2020. https://doi.org/10.1146/annurev-biodatasci-030320-040844.

      is:article lang:en social media healthcare pharmacovigilance sentiment analysis biomedicine social media mining epidemiology
    Visit annotations in context

    Tags

    Annotators

    URL

    annualreviews.org/doi/10.1146/annurev-biodatasci-030320-040844