| dc.contributor.author | Ullah, Md. Shihab | |
| dc.contributor.author | Akter, Rojoni | |
| dc.date.accessioned | 2025-08-28T07:01:02Z | |
| dc.date.available | 2025-08-28T07:01:02Z | |
| dc.date.issued | 2024-07-24 | |
| dc.identifier.uri | http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/14019 | |
| dc.description | Project report | en_US |
| dc.description.abstract | The purpose of this study is to determine when a new entrepreneur wants to start a business in social media, he or she will know which social media platform is best for business. Based on collected data (We collected data using Google Forms as well as a paper copy of this form) and used machine learning techniques to find the accuracy. We also use a real dataset to run simulations to determine which social media site is best for a new entrepreneur. The Regression model is also used to determine the actual social platform. Using the best algorithm possible improves diffusion performance. Integrating simulations to create a real-time decision assistance platform will improve the efficiency of business diffusion. Finally, we received the outcome. We forecasted what is best for a new entrepreneur looking to launch a new internet business and advertise their brand. If we use more data (2 lack or 3 lack), in that situation the accuracy could be different. But even after we took more data our accuracy and target were same. This study is especially based on university students' feedback. The majority of those who responded to our survey, 81%, were under the age of 25. | en_US |
| dc.description.sponsorship | DIU | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | Daffodil International University | en_US |
| dc.subject | Natural Language Processing (NLP) | en_US |
| dc.subject | Social Media Analytics | en_US |
| dc.subject | Influencer Marketing | en_US |
| dc.subject | Deep Learning | en_US |
| dc.title | Project on Finding the Best Social Media Platform for Social Media Marketing using Machine Learning | en_US |
| dc.type | Other | en_US |