1. Shodhganga@INFLIBNET
  2. Jaypee Institute of Information Technology
  3. Department of Computer Science Engineering and Information Technology
Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/250064
Title: Information Diffusion Framework for Virality Prediction of Social Media Content
Researcher: Aggrawal, Niyati
Guide(s): Arora, Anuja
Keywords: Brand analysis
Engineering and Technology,Computer Science,Computer Science Information Systems
Growth Model
influential
mathematical model
Measuring information
social networking
View Count Model
Virality Model
YouTube
University: Jaypee Institute of Information Technology
Completed Date: 22/05/2019
Abstract: included newline
Pagination: 
URI: http://hdl.handle.net/10603/250064
Appears in Departments:Department of Computer Science Engineering and Information Technology

Files in This Item:
File Description SizeFormat 
01_title.pdfAttached File2.38 MBAdobe PDFView/Open
02_table of contents.pdf58.47 kBAdobe PDFView/Open
03_declaration.pdf52.61 kBAdobe PDFView/Open
04_certificate.pdf52.58 kBAdobe PDFView/Open
05_acknowledgement.pdf82.12 kBAdobe PDFView/Open
06_abstract.pdf55.54 kBAdobe PDFView/Open
07_list of abbreviations and symbols.pdf117.17 kBAdobe PDFView/Open
08_list of figures, tables and algorithms.pdf94.24 kBAdobe PDFView/Open
09_chapter1.pdf552.86 kBAdobe PDFView/Open
10_chapter2.pdf375.4 kBAdobe PDFView/Open
11_chapter3.pdf3.9 MBAdobe PDFView/Open
12_chapter4.pdf1.05 MBAdobe PDFView/Open
13_chapter5.pdf551.25 kBAdobe PDFView/Open
14_chapter6.pdf2.49 MBAdobe PDFView/Open
15_chapter7.pdf124.26 kBAdobe PDFView/Open
16_bibliography.pdf89.11 kBAdobe PDFView/Open
17_list of publications.pdf78.49 kBAdobe PDFView/Open
18_synopsis.pdf2.44 MBAdobe PDFView/Open
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