Please use this identifier to cite or link to this item:
http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/10192
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DC Field | Value | Language |
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dc.contributor.author | Tyagi, Ajay | - |
dc.contributor.author | Srivastava, Devbrat | - |
dc.contributor.author | Verma, Ruchi [Guided by] | - |
dc.date.accessioned | 2023-09-30T09:49:24Z | - |
dc.date.available | 2023-09-30T09:49:24Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/10192 | - |
dc.description | Enrollment No. 191525, 191540 | en_US |
dc.description.abstract | This essay discusses social media's growth, user demographics, and advantages. Many social media platforms are now being used efficiently, and the data from these platforms also aids in revealing hidden facts through analysis. In social computational science, which aids people in decision-making, data analysis is crucial. Big data analytics on social media is often known as social media data analytics or just social media analytics, and it offers analysts great opportunity to come up with original concepts and recognize new patterns. The many forms of social media analysis, as well as the widely used technologies for social media analytics, are also covered in this study. Also mentioned are the numerous research difficulties associated with studying social media. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Jaypee University of Information Technology, Solan, H.P. | en_US |
dc.subject | Social media | en_US |
dc.subject | Decision making | en_US |
dc.subject | Logistic regression | en_US |
dc.subject | K- nearest neighbor | en_US |
dc.title | Social Media Analytics for Business Decision Making | en_US |
dc.type | Project Report | en_US |
Appears in Collections: | B.Tech. Project Reports |
Files in This Item:
File | Description | Size | Format | |
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Social Media Analytics for Business Decision Making.pdf | 2.44 MB | Adobe PDF | View/Open |
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