Search (2 results, page 1 of 1)

  • × author_ss:"Du, Q."
  • × year_i:[2020 TO 2030}
  1. Du, Q.; Li, J.; Du, Y.; Wang, G.A.; Fan, W.: Predicting crowdfunding project success based on backers' language preferences (2021) 0.03
    0.03443813 = product of:
      0.06887626 = sum of:
        0.021487473 = weight(_text_:science in 415) [ClassicSimilarity], result of:
          0.021487473 = score(doc=415,freq=2.0), product of:
            0.12305341 = queryWeight, product of:
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.0467152 = queryNorm
            0.17461908 = fieldWeight in 415, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.046875 = fieldNorm(doc=415)
        0.04738879 = product of:
          0.09477758 = sum of:
            0.09477758 = weight(_text_:history in 415) [ClassicSimilarity], result of:
              0.09477758 = score(doc=415,freq=4.0), product of:
                0.21731828 = queryWeight, product of:
                  4.6519823 = idf(docFreq=1146, maxDocs=44218)
                  0.0467152 = queryNorm
                0.43612334 = fieldWeight in 415, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  4.6519823 = idf(docFreq=1146, maxDocs=44218)
                  0.046875 = fieldNorm(doc=415)
          0.5 = coord(1/2)
      0.5 = coord(2/4)
    
    Abstract
    Project success is critical in the crowdfunding domain. Rather than the existing project-centric prediction methods, we propose a novel backer-centric prediction method. We identify each backer's preferences based on their pledge history and calculate the cosine similarity between backer's preferences and the project as each backer's persuasibility. Finally, we aggregate all the backers' persuasibility to predict project success. To validate our method, we crawled data on 183,886 projects launched during or before December 2014 on Kickstarter, a crowdfunding website. We selected 4,922 backers with a total of 442,793 pledges to identify backers' preferences. The results show that a backer is more likely to be persuaded by a project that is more similar to the backer's preferences. Our findings not only demonstrate the efficacy of backers' pledge history for predicting crowdfunding project success but also verify that a backer-centric method can supplement the existing project-centric approaches. Our model and findings enable crowdfunding platform agencies, fund-seeking entrepreneurs, and investors to predict the success of a crowdfunding project.
    Source
    Journal of the Association for Information Science and Technology. 72(2021) no.12, S.1558-1574
  2. Liu, Q.; Yang, Z.; Cai, X.; Du, Q.; Fan, W.: ¬The more, the better? : The effect of feedback and user's past successes on idea implementation in open innovation communities (2022) 0.00
    0.004476557 = product of:
      0.017906228 = sum of:
        0.017906228 = weight(_text_:science in 497) [ClassicSimilarity], result of:
          0.017906228 = score(doc=497,freq=2.0), product of:
            0.12305341 = queryWeight, product of:
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.0467152 = queryNorm
            0.1455159 = fieldWeight in 497, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.0390625 = fieldNorm(doc=497)
      0.25 = coord(1/4)
    
    Source
    Journal of the Association for Information Science and Technology. 73(2022) no.3, S.376-392

Authors