Yildiz, T. K.Atagün, E.Bayiroğlu, H.Timuçin, T.Gündüz, H.2021-12-012021-12-01202123674512https://doi.org/10.1007/978-3-030-79357-9_33https://hdl.handle.net/20.500.12684/9921Kickstarter is a platform that supports the transformation of projects into products by embracing entrepreneurial investor interaction. Entrepreneurs who register on the Kickstarter website exhibit presentations and visuals on their projects. People who work or have new ideas in the fields of art, comics, design, technology, film, games, music and publishing are looking for support to improve their ideas. Entrepreneurs display the project details in a textual expression in order to attract investors’ interest. Investors make a decision to invest in the project by reading these expressions and consider them logically. Investors need to solve the difficulties they encountered in decision-making through various artificial intelligence or language processing methods. Natural Language Processing (NLP) is one of the preferred methods for such decision-making problems. In this study, NLP techniques and word attributes were obtained from the explanations of the projects in order to provide support to the investors. In addition, temporal attributes were extracted by considering the start and end times of the projects. According to these attributes, whether the projects can reach the targeted budget has been determined by artificial learning methods and predictable effects of some words or phrases in reaching the targeted budget have been highlighted. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.en10.1007/978-3-030-79357-9_33info:eu-repo/semantics/closedAccessKickstarterNatural Language ProcessingText miningBook Chapter763443492-s2.0-85109954373Q3