Social Media Influence Analysis using Data Science Techniques

The major purpose of this literature search report is to demonstrate the usage of different tactics of data science to investigate impact of social media while considering the interaction between influences and their followers.

1. Research Purpose
The major objective of this report is to investigate
different primary research relevant to the role of
data science is social media networks.
Background Context
One of the major reason due to which social media network’s
control deceits in its data. And for this reason, they require
majority of it as their tendency to persuade end-users to
exchange data relevant to every single moment.
Scheduling of Task
Research Methodology
This research implements a systematic literature
review and tracks a transparent and scientific
procedure during the research utilizing secondary
data.
Evaluation Methodology
our major focus was only to recognize the main
concerns and identify persuasive research on the
title of the study. Regarding the selection of
research papers, we conducted a citation
frequency investigation to regulate which
research should be included and circulate the
basis of purpose statement.
Professional, legal and
Ethical issues
Throughout the whole process of research, we
have not excluded any discipline and involved all
disciplines fulfilling the criteria of enclosure.
Resources of Selection
SOCIAL MEDIA INFLUENCE ANALYSIS USING DATA SCIENCE TECHNIQUES
1. To recognize applications of IoT and big data.
2. To discover innovative characteristics of IoT and big
data focusing on real time analytics of stream and
event data.
3. To explore the interoperability, privacy and security
challenges in managing big data in an IoT environment.
4. To elaborate anticipated solutions, frameworks and
architectures.
1. To recognize applications of IoT and big data.
2. To discover innovative characteristics of IoT and big
data focusing on real time analytics of stream and
event data.
3. To explore the interoperability, privacy and security
challenges in managing big data in an IoT environment.
4. To elaborate anticipated solutions, frameworks and
architectures.
Reference
Al-Qurishi, M., Alhuzami, S., AlRubaian, M., Hossain, M.S., Alamri, A. and
Rahman, M.A., 2018. User profiling for big social media data using
standing ovation model. Multimedia Tools and Applications, 77, pp.11179-
11201.
Ghani, N.A., Hamid, S., Hashem, I.A.T. and Ahmed, E., 2019. Social media
big data analytics: A survey. Computers in Human behavior, 101, pp.417-
428.