Predicting Anime Success: Spotting Future Hits

Oct 4, 2024 · how algorithms like linear regression and decision trees can forecast an anime’s success. Consumers of anime will most likely check the description of anime first before deciding to watch it, so understanding what basic genres are the most attractive to audiences will benefit these. With this much relevance behind anime, this paper proposes some observations of genres which trend over time. This is mostly to help creative teams behind anime studios to appeal to. One of the most groundbreaking approaches in recent times involves leveraging artificial intelligence (ai) to predict the next big anime hit.

This project aims to maximize studios’ profits on animes they produce by estimating 'mean' rating of animes and predicting 'success' probability before production, hence giving studios the. This paper proposes sentiment analysis to help business leaders make their decisions about investing in this field and the anime producers to understand viewers' feelings and how satisfied they are. Deep learning techniques are utilized to develop a text sentiment analysis model to. Nov 23, 2024 · predicting anime ratings and popularity using machine learning: This project aims to explore the factors that influence the success of anime and manga using machine learning techniques. The dataset is obtained from myanimelist and includes user. Mar 30, 2021 · deep learning techniques are utilized to develop a text sentiment analysis model to classify reviews into positive and negative classes. A data set containing 50,000 reviews from. For predicting the success of an anime in its early stages of development, a baseline is proposed in this paper, based on the synopsis of its plot. Anisyn7 is presented, which is a corpus.