Artificial Intelligence Studies https://www.aistudies.org/index.php/ais <p>Artificial Intelligence Studies (AIS) is an International Refereed Journal published in any field releated to Artificial Intelligence.The objective of AIS is to be able to hear scientific studies both at&nbsp; international academic and industrial organizations.</p> en-US <p>Artificial Intelligence Studies (AIS) publishes open access articles under a Creative Commons Attribution 4.0 International License (CC BY). This license permits user to freely share (copy, distribute and transmit) and adapt the contribution including for commercial purposes, as long as the author is properly attributed.</p> <p><img style="width: 88px;" src="https://licensebuttons.net/l/by/4.0/88x31.png" alt="88x31.png"></p> <p><strong style="font-size: .9em;">&nbsp;</strong><strong>For all licenses mentioned above, authors can retain copyright and all publication rights without restriction.&nbsp;</strong></p> <p><strong>&nbsp;</strong></p> <p>&nbsp;</p> editorial@aistudies.org (Editorial Office) enes@parantezteknoloji.com.tr (M. Enes KALE) Sun, 31 Dec 2023 00:00:00 +0000 OJS 3.1.1.2 http://blogs.law.harvard.edu/tech/rss 60 Prediction with deep learning neural networks: the careers in show business https://www.aistudies.org/index.php/ais/article/view/65 <div class="page" title="Page 1"> <div class="layoutArea"> <div class="column"> <p>In this article, we investigate whether we can predict individual success in the film industry by using four distinct deep learning neural networks. It is shown that the highest rates of accuracy in prediction can be obtained through using the bidirectional deep learning algorithms. We found that when the prediction is taken into account, there is no gender bias. These findings can be explained by the fact that the film industry is essentially dominated by the popularity for both actors and actresses. Moreover, since popularity, to a greater extent, determines success, bidirectional algorithms are more effective in predicting success due to the fact that they are able to take into account both past and future information regarding a particular data point. This is a must in predict- ing success in the film industry, since popularity and its lack thereof determines success and failure in the past as well as in the future of an acting career</p> </div> </div> </div> Ali Can GÜNHAN, Kamil TOPAL ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc/4.0 https://www.aistudies.org/index.php/ais/article/view/65 Sun, 31 Dec 2023 13:36:08 +0000