Search (2 results, page 1 of 1)

  • × author_ss:"Wang, X."
  • × year_i:[2020 TO 2030}
  1. Walsh, J.A.; Cobb, P.J.; Fremery, W. de; Golub, K.; Keah, H.; Kim, J.; Kiplang'at, J.; Liu, Y.-H.; Mahony, S.; Oh, S.G.; Sula, C.A.; Underwood, T.; Wang, X.: Digital humanities in the iSchool (2022) 0.01
    0.008998952 = product of:
      0.017997904 = sum of:
        0.017997904 = product of:
          0.035995807 = sum of:
            0.035995807 = weight(_text_:j in 463) [ClassicSimilarity], result of:
              0.035995807 = score(doc=463,freq=4.0), product of:
                0.14500295 = queryWeight, product of:
                  3.1774964 = idf(docFreq=5010, maxDocs=44218)
                  0.045634337 = queryNorm
                0.2482419 = fieldWeight in 463, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.1774964 = idf(docFreq=5010, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=463)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
  2. Wang, X.; Zhang, M.; Fan, W.; Zhao, K.: Understanding the spread of COVID-19 misinformation on social media : the effects of topics and a political leader's nudge (2022) 0.01
    0.0076358644 = product of:
      0.015271729 = sum of:
        0.015271729 = product of:
          0.030543458 = sum of:
            0.030543458 = weight(_text_:j in 549) [ClassicSimilarity], result of:
              0.030543458 = score(doc=549,freq=2.0), product of:
                0.14500295 = queryWeight, product of:
                  3.1774964 = idf(docFreq=5010, maxDocs=44218)
                  0.045634337 = queryNorm
                0.21064025 = fieldWeight in 549, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.1774964 = idf(docFreq=5010, maxDocs=44218)
                  0.046875 = fieldNorm(doc=549)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    The spread of misinformation on social media has become a major societal issue during recent years. In this work, we used the ongoing COVID-19 pandemic as a case study to systematically investigate factors associated with the spread of multi-topic misinformation related to one event on social media based on the heuristic-systematic model. Among factors related to systematic processing of information, we discovered that the topics of a misinformation story matter, with conspiracy theories being the most likely to be retweeted. As for factors related to heuristic processing of information, such as when citizens look up to their leaders during such a crisis, our results demonstrated that behaviors of a political leader, former US President Donald J. Trump, may have nudged people's sharing of COVID-19 misinformation. Outcomes of this study help social media platform and users better understand and prevent the spread of misinformation on social media.