launch hard or go home! · 2019-12-14 · launch hard or go home! predicting the success of...
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Launch Hard or Go Home!Predicting the Success of Kickstarter Campaigns
COSN'13October 8th, 2013
Vincent Etter, Matthias Grossglauser, Patrick ThiranEPFL, Lausanne, Switzerland
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What is Kickstarter?• Crowdfunding website
• Raise money to launch creative projects
• Each campaign has:
• a funding goal
• a campaign duration
• All-or-nothing funding model
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A Success Story
• Since its launch in 2009:
• 50,000 projects successfully funded
• 44% success rate
• $811,000,000 raised
• 4,900,000 backers
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Our Dataset
• Discover campaigns on the "Recently Launched" page
• Regularly get their status: number of backers, amount of money pledged
• Monitor Twitter in parallel for all tweets containing keyword kickstarter
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Our Dataset• From September 2012 to May 2013:
• 16,042 campaigns
• 48.24% of successful campaigns
• 1,309,295 backers
• $158,026,656 pledged
• 737,398 "kickstarter" tweets
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Our Predictors
• Baseline: campaigns' static attributes [1]
• Two sources of information:
• Money: kNN, Markov
• Social: tweets, project/backer graph
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[1] M. Greenberg et al. Crowdfunding support tools: predicting success & failure. In CHI'13 Extended Abstracts. ACM, 2013.
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Graph Predictor• Can we use backers as source of
information?
• Consider the project/backer graph:
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Graph Predictor• Extract several features:
• # of backers
• #/prop. of first-time backers
• # projects with co-backers
• #/prop. of these that are successful
• Train a Support Vector Machine
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Prediction Accuracy
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kNNMarkov
Graph
TweetsBaseline
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Combined Predictor
• Money-based results are quite good
• Can we use social predictors to help?
• Train a SVM to combine individual predictions
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Combiner Results
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Conclusion
• Combiner improves early predictions
• There is potential in social predictors
• Future work:
• Improve graph predictor
• Take dynamics on Twitter and project/backer graph into account
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Thank you!
Data and real-time predictions onhttp://sidekick.epfl.ch
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