{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T03:27:50Z","timestamp":1768015670732,"version":"3.49.0"},"reference-count":25,"publisher":"Emerald","issue":"4","license":[{"start":{"date-parts":[[2020,7,27]],"date-time":"2020-07-27T00:00:00Z","timestamp":1595808000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJWIS"],"published-print":{"date-parts":[[2020,7,27]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>This study aims to analyze Kickstarter data along with social media data from a data mining perspective. Kickstarter is a crowdfunding financing plataform and is a form of fundraising and is increasingly being adopted as a source for achieving the viability of projects. Despite its importance and adoption growth, the success rate of crowdfunding campaigns was 47% in 2017, and it has decreased over the years. A way of increasing the chances of success of campaigns would be to predict, by using machine learning techniques, if a campaign would be successful. By applying classification models, it is possible to estimate if whether or not a campaign will achieve success, and by applying regression models, the authors can forecast the amount of money to be funded.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>The authors propose a solution in two phases, namely, launching and campaigning. As a result, models better suited for each point in time of a campaign life cycle.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>The authors produced a static predictor capable of classifying the campaigns with an accuracy of 71%. The regression method for phase one achieved a 6.45 of root mean squared error. The dynamic classifier was able to achieve 85% of accuracy before 10% of campaign duration, the equivalent of 3\u2009days, given a campaign with 30\u2009days of length. At this same period time, it was able to achieve a forecasting performance of 2.5 of root mean squared error.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>The authors carry out this research presenting the results with a set of real data from a crowdfunding platform. The results are discussed according to the existing literature. This provides a comprehensive review, detailing important research instructions for advancing this field of literature.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/ijwis-05-2020-0026","type":"journal-article","created":{"date-parts":[[2020,7,24]],"date-time":"2020-07-24T09:24:27Z","timestamp":1595582667000},"page":"387-412","source":"Crossref","is-referenced-by-count":6,"title":["Success prediction of crowdfunding campaigns: a two-phase modeling"],"prefix":"10.1108","volume":"16","author":[{"given":"Lafaiet","family":"Silva","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"N\u00e1dia F\u00e9lix","family":"Silva","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thierson","family":"Rosa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2020100708375150700_ref001","article-title":"Trends show crowdfunding to surpass vc in 2016","volume":"6","year":"2015","journal-title":"Forbes"},{"key":"key2020100708375150700_ref002","article-title":"Enriching word vectors with subword information","year":"2016","journal-title":"CoRR"},{"issue":"1","key":"key2020100708375150700_ref003","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","year":"2001","journal-title":"Machine Learning"},{"key":"key2020100708375150700_ref004","article-title":"Crowdfunding as a novel financial tool for district","year":"2018"},{"key":"key2020100708375150700_ref005","first-page":"115","article-title":"The determinants of crowdfunding success: evidence from technology projects","volume":"181","year":"2015","journal-title":"Procedia - Social and Behavioral Sciencesproceedings of the 3rd international conference on leadership, technology and innovation management"},{"key":"key2020100708375150700_ref006","unstructured":"Etter, V. 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