A machine learning approach to predict movie success from youtube trailer comments
| bracu.type.group | Research Publications | |
| datacite.rights | Metadata Only | |
| dc.contributor.author | Khan, Farden Ehsan | |
| dc.contributor.author | Ruhan, Ahmed Mahir | |
| dc.contributor.author | Shamsuddin, Rifat | |
| dc.contributor.author | Ashraf, Faisal Bin | |
| dc.contributor.department | Department of Computer Science and Engineering | |
| dc.date.accessioned | 2026-09-29T10:22:57Z | |
| dc.date.available | 2026-09-29T10:22:57Z | |
| dc.date.issued | 2022-01-01 | |
| dc.description.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. | |
| dc.description.version | Published | |
| dc.format.extent | 6 Pages | |
| dc.identifier.citation | F. E. Khan, A. M. Ruhan, R. Shamsuddin and F. B. Ashraf, "A Machine Learning Approach to Predict Movie Success from Youtube Trailer Comments," 2022 25th International Conference on Computer and Information Technology (ICCIT), Cox's Bazar, Bangladesh, 2022, pp. 372-377, doi: 10.1109/ICCIT57492.2022.10055275. | |
| dc.identifier.doi | 10.1109/ICCIT57492.2022.10055275 | |
| dc.identifier.issn | 9798350346022 | |
| dc.identifier.other | 2-s2.0-85150170796 | |
| dc.identifier.uri | https://hdl.handle.net/10361/30298 | |
| dc.language.iso | en_US | |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | |
| dc.relation.hasversion | 10.1109/ICCIT57492.2022.10055275 | |
| dc.relation.ispartof | Proceedings of 2022 25th International Conference on Computer and Information Technology Iccit 2022 | |
| dc.relation.ispartofseries | Proceedings of 2022 25th International Conference on Computer and Information Technology Iccit 2022 | |
| dc.relation.uri | https://ieeexplore.ieee.org/document/10055275 | |
| dc.subject | Social networking (online) | |
| dc.subject | Motion pictures | |
| dc.subject | Prediction algorithms | |
| dc.subject | Social media | |
| dc.subject | Deep learning | |
| dc.subject | Trend analysis | |
| dc.subject | Text mining | |
| dc.subject | Random forest | |
| dc.subject | Sentiment analysis | |
| dc.subject | Decision tree | |
| dc.subject.lcsh | Online social networks. | |
| dc.subject.lcsh | Sentiment analysis. | |
| dc.title | A machine learning approach to predict movie success from youtube trailer comments | |
| dc.type | Conference Proceeding | |
| person.affiliation.name | BRAC University | |
| person.affiliation.name | BRAC University | |
| person.affiliation.name | BRAC University | |
| person.affiliation.name | BRAC University | |
| person.identifier.scopus-author-id | 58143568400 | |
| person.identifier.scopus-author-id | 58143724700 | |
| person.identifier.scopus-author-id | 58144340900 | |
| person.identifier.scopus-author-id | 57194202985 |