A new approach to achieve the users’ habitual opportunities on social media
| Dublin Core | PKP Metadata Items | Metadata for this Document | |
| 1. | Title | Title of document | A new approach to achieve the users’ habitual opportunities on social media |
| 2. | Creator | Author's name, affiliation, country | Arif Ridho Lubis; Universitas Sumatera Utara; Indonesia |
| 2. | Creator | Author's name, affiliation, country | Mahyuddin K. M. Nasution; Universitas Sumatera Utara; Indonesia |
| 2. | Creator | Author's name, affiliation, country | Opim Salim Sitompul; Universitas Sumatera Utara; Indonesia |
| 2. | Creator | Author's name, affiliation, country | Elviawaty Muisa Zamzami; Universitas Sumatera Utara; Indonesia |
| 3. | Subject | Discipline(s) | |
| 3. | Subject | Keyword(s) | Approach; Habitual; Naïve Bayes; Probability |
| 4. | Description | Abstract | The data generated from social media is very large, while the use of data from social media has not been fully utilized to become new knowledge. One of the things that can become new knowledge is user habits on social media. Searching for user habits on Twitter by using user tweets can be done by using modeling, the use of modeling lies when the data has been preprocessed, and the ranking will then be checked in the dictionary, this is where the role of the model is carried out to get a chance that the words that have been ranked will perform check the word in the dictionary. The benefit of the model in general is to get an understanding of the mechanism in the problem so that it can predict events that will arise from a phenomenon which in this case is user habits. So that with the availability of this model, it can be a model in getting opportunities for user habits on Twitter social media. |
| 5. | Publisher | Organizing agency, location | Institute of Advanced Engineering and Science |
| 6. | Contributor | Sponsor(s) | |
| 7. | Date | (YYYY-MM-DD) | 2023-03-01 |
| 8. | Type | Status & genre | Peer-reviewed Article |
| 8. | Type | Type | |
| 9. | Format | File format | |
| 10. | Identifier | Uniform Resource Identifier | https://ijai.iaescore.com/index.php/IJAI/article/view/22167 |
| 10. | Identifier | Digital Object Identifier (DOI) | http://doi.org/10.11591/ijai.v12.i1.pp41-47 |
| 11. | Source | Title; vol., no. (year) | IAES International Journal of Artificial Intelligence (IJ-AI); Vol 12, No 1: March 2023 |
| 12. | Language | English=en | |
| 14. | Coverage | Geo-spatial location, chronological period, research sample (gender, age, etc.) | |
| 15. | Rights | Copyright and permissions |
Copyright (c) 2022 Institute of Advanced Engineering and Science This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. |