Farden Ehsan Khan, Ahmed Mahir Ruhan, Rifat Shamsuddin, Faisal Bin Ashraf
{"title":"从Youtube预告片评论中预测电影成功的机器学习方法","authors":"Farden Ehsan Khan, Ahmed Mahir Ruhan, Rifat Shamsuddin, Faisal Bin Ashraf","doi":"10.1109/ICCIT57492.2022.10055275","DOIUrl":null,"url":null,"abstract":"Social media use has increased to such levels in recent years that it has transformed into a trend-setting powerhouse, introducing subjects that would have previously remained outside of the public eye. Through people’s shared opinions and responses about a trend on social media, we hope to determine how long it can hold an audience’s attention on its own. We will analyze the sentiment of individuals toward a particular topic using the information gleaned from social media comments. Our work will be based on unreleased films and make predictions about how they will turn out when they are released. In this work, we have processed and examined accumulated reviews about a film to see whether the general public feels positively or negatively about it and to calculate the likelihood that a certain film will be a success. From this, we can infer how the success of a movie or product is influenced by both positive and negative attention before its release.","PeriodicalId":255498,"journal":{"name":"2022 25th International Conference on Computer and Information Technology (ICCIT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Machine Learning Approach to Predict Movie Success from Youtube Trailer Comments\",\"authors\":\"Farden Ehsan Khan, Ahmed Mahir Ruhan, Rifat Shamsuddin, Faisal Bin Ashraf\",\"doi\":\"10.1109/ICCIT57492.2022.10055275\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Social media use has increased to such levels in recent years that it has transformed into a trend-setting powerhouse, introducing subjects that would have previously remained outside of the public eye. Through people’s shared opinions and responses about a trend on social media, we hope to determine how long it can hold an audience’s attention on its own. We will analyze the sentiment of individuals toward a particular topic using the information gleaned from social media comments. Our work will be based on unreleased films and make predictions about how they will turn out when they are released. In this work, we have processed and examined accumulated reviews about a film to see whether the general public feels positively or negatively about it and to calculate the likelihood that a certain film will be a success. From this, we can infer how the success of a movie or product is influenced by both positive and negative attention before its release.\",\"PeriodicalId\":255498,\"journal\":{\"name\":\"2022 25th International Conference on Computer and Information Technology (ICCIT)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 25th International Conference on Computer and Information Technology (ICCIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIT57492.2022.10055275\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 25th International Conference on Computer and Information Technology (ICCIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIT57492.2022.10055275","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Machine Learning Approach to Predict Movie Success from Youtube Trailer Comments
Social media use has increased to such levels in recent years that it has transformed into a trend-setting powerhouse, introducing subjects that would have previously remained outside of the public eye. Through people’s shared opinions and responses about a trend on social media, we hope to determine how long it can hold an audience’s attention on its own. We will analyze the sentiment of individuals toward a particular topic using the information gleaned from social media comments. Our work will be based on unreleased films and make predictions about how they will turn out when they are released. In this work, we have processed and examined accumulated reviews about a film to see whether the general public feels positively or negatively about it and to calculate the likelihood that a certain film will be a success. From this, we can infer how the success of a movie or product is influenced by both positive and negative attention before its release.