Social Media Influence Analysis using Data Science Techniques

Social Media Influence Analysis using Data
Science Techniques

Contents
1. Introduction...................................................................................................................................4
2. Literature Search..........................................................................................................................5
Database one: ACM digital library.................................................................................................7
Database Two: Science Direct........................................................................................................11
Database Three: Springer ..............................................................................................................15
3. Selection Criteria ........................................................................................................................21
4. Conclusion ...................................................................................................................................26
References............................................................................................................................................28

1. Introduction
In today’s technological era, the usage of social media networks is rising quickly and
boundlessly, these SM networks are considered as a significant pool for unsorted data in
massive quantity. Social media effect determines its influencer’s ability to inspire a group of
people’s thought, emotional state and features in operational and structured societies. The
exploratory research on the inspirational activities impacts multiple types of areas from
numerous perceptions which includes tactical planning and concluding results unless
generation and delivery of the product. 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. Subsequently a
critical evaluation of approximately fifty-five research papers we conducted that four data
representation models have been utilized with SM networks and ten 10 data investigative
tactics to report six different kinds of research aims considering more than twenty area. Based
on the prior literature, graph was regarded as the most utilized data investigative tactic and data
representation model while considering the relationship between connectivity and end-users.
Social media is regarded as a cluster of internet-based application which are created on the
technological and ideological framework of Web 2.0. One major feature of social media
network is that it initializes the production and argument of content created but end-users. The
main distinctive characteristic in social media impacting the professional corporations may be
exactly the truth that the networks and content are generated by users.
Based on Statista study (H. Tankovska, 2017), approximately 3.6 billion individuals were
utilizing social media networks all over the globe which was raised to around 4,41 billion by
2025. The report demonstrated that approximately 4.57 billion individuals around the globe
utilizes the internet service among those nearly 346 million new users came online prior to one
year.
The users of internet allocate around 144 minutes as an average on a social media per 24 hours.
The procedure of mining and investigating social media networks facilitates in collecting data
which enhance impact growth.
Different social media networks are utilized by people to communicate with people all over the
globe to familiarize themselves to others by exposing their daily live update and follow
different pages and channels. This impulsive behaviour generated which is nowadays
recognized as influencers that alters, the way that corporation interact with their users. This
research facilitates in selecting the accurate representation framework and analytics procedure
which coordinates with analysis perspective and connects with specialized platforms. The best
possible procedure to response certain query of efficiency contrasting different literature
studies is to generate a literature search report.
The major objective of this report is to investigate different primary researches relevant to role
of data science is social media networks the given research queries were generated.

• RQ1: Which procedures have been cast-off to investigate users associated data in social
media?
• RQ2: What is the aim of investigating users associated data in social media?
• RQ3: How is it probable to practise investigating methods while considering interactions
between followers and influencers?
2. Literature Search
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. The huge pool of information at the removal of social
media organizations reflects thus people interact with each other and at the midpoint of these
coordination resides worthless data relevant to what individuals and communities possess
important. This amount of information, along with the rapid rate of information stream that SM
is famous for, shows the basis of huge data. By implementing analytics techniques of data
science to the bulk of information produced through social media, huge information
applications in multiple area move on the distant side the method of coordinating to viewing
this the information present within the coordination may possess an impact on organizational
performance and individual’s read of a whole. The techniques of data science help
organizations to minimize unnecessary data from the insightful information that users upload.
As an instance, analytical techniques will be automated to track the positive or negative opinion
a couple of whole as this may portend revenue and name.
As a bulk of information is gathered from multiple sources it is predictable that the majority of
data is gathered from amorphous source. Subsequently, social media networks are considered
to produce the most significant stream of amorphous data. Such as comments, likes, views,
subscriptions and all other activities which users perform on different social media platforms
will be gathered and investigated by concerned groups. One main feature of social media
network is that it adjusts the production and dispute of content created but end-users. The main
distinctive characteristic in social media impacting the professional corporations may be
precisely the truth that the networks and content are generated by users.
In this era of digitalization, social media networks are vital for different businesses. Preserving
an occurrence on mediums such as Twitter and LinkedIn are vital as a consequence of it allows
people to coordinate with the organization on deceptively confidential level which helps
businesses through numerous leads. Collectively it is important for the representative user.
Approximately, 2 billion monthly clients are boasted by Facebook itself relating to 26 of the
whole globe population. Therefore, it is necessary to ponder over the fact that huge amount of
information is gathered from social media platforms in an incredible range of arrangements.
According to a research, huge information investigations facilitate corporation to utilize their
data to find innovative opportunities (Sahatiya, 2018). Consequently, it provides a smarter

business interchange, supplementary economical functionality, high revenues and satisfied
customers. Moreover, in this study Tom Davenport director of analysis IIA interrogated around
50 different businesses to know about huge information in big organizations. Thus, they
utilized the following approaches:
1. Cost minimization: huge information technologies such as cloud-based analysis and
Hadoop created significant value aids once it includes loading huge amount of
information and they would recognize supplementary economical methods of
enhancing business.
2. Rapid and high perceptive procedure: Different business industries are capable to
investigate data and create selections reinforced with what they have acquired due to
high speed of in-memory analytics and Hadoop. These technologies are constituted
with the elasticity to analyze innovative sources of knowledge.
3. Innovative service and products: The services which customers require to fulfill their
needs and attain satisfaction can easily be achieved with the flexibility of data analytics.
Tom Davenport observed that with huge information investigation, supplementary
organization’s field unit generating innovative products to satisfy customer’s needs.
Subsequently, a huge amount of exploratory research, some reviews on social media analytics
already present in prior literatures. A recent research conducted demonstrated how advantages
can be created through analysis of data produced by social media networks along with different
challenges. Moreover, a literature review conducted in 2017 shows how social media analytics
reinforced decision making (Rathore et al., 2017). The researcher demonstrated different
analytical methods which are utilized in numerous circumstances for improved decision
making. Additionally, they utilized approaches that are often used but possess higher potential
for enhanced decision making. Besides these studies on unambiguous application units can be
observed in former literature studies. A research on social media analytics in healthcare
demonstrates the utility and benefits of data science in this sector. In contrast a study found in
2018 showed the potentials of utilizing social media analytics to manage disaster circumstances
(Wang and Ye, 2018). For the classification of the literature, they recommended a framework
that related to the 4 most related areas in managing disaster situations.
Moreover, there are numerous research that observed different issues in the area of social media
analysis which can be resolved using data science application. An existing study recognized
different analytics tools and technologies from the sector of data science (Sahatiya, 2018). A
cluster of issues suffered by researchers in this area of studies can be identified in an article
published in 2018 (Stieglitz et al., 2018). The outcomes showed that the main issue found in
the detection, gathering and creation of social media data. They utilized their outcomes to
expand a prior framework model for social media analytics. An analogous aim is chased by an
author in 2018. In the first state of analysis, they observed that there is a need of evidently
defined guides for social media data analysis (Sebei et al., 2018). They considered it as a chance
to recognize technologies in the sophisticated research area of data science which can be
utilized for the social media analytics. The prior research demonstrates the relevance but
besides this complexity of the research requires in the area of social media analytics. There is

numerous research which related to solitary application sectors such as natural disaster and
health or those which focuses on particular approaches in a special application sector.
Based on prior literature reviews there is no solitary technological tool or procedure which
incorporates huge informative analysis. Thus, there are numerous sophisticated techniques of
data science which can be implemented to huge amount of information. Nevertheless,
fundamentally multiple types of technologies work by side to guide researchers to get the
highest value from collected data. The following are some main concepts of data science in
analyzing data:
 Management of Data
 Data mining
 In-memory analytics
 Predictive analysis
 Text mining
The literature search report approach combines the core concepts of research queries to attain
accurate outcomes. This synopsis initiated with an organized construction of different
keywords which included social media, followers, influencers, data science, analysis,
innovative analytical techniques used to explore three databases ACM Digital library, Springer
and Science Direct. Besides we also added different synonyms, alterations and relevant terms
for each defined keyword. Moreover, the usage of Boolean operator AND and OR allowed us
to search combination of different terms.
Database one: ACM digital library
Numbe
r
Keywords Title Filters Numbe
r of
related
articles
Notes
1 Interaction
s
Cross-platform
Interactions and
Popularity in the Live-
streaming Community
Year: 2019
Content:
Conference
100 Tests were performed on
the community-proposed
relationship between
behavior on social media
accounts and popularity
through examining the
timing of creation and use
of social media accounts.
2 Social
networks
Role of conformity in
opinion dynamics in
social networks
Year:2014
Content:
Conference
100 Identified thehe problem of
estimating these conformity
values for users, using only
the expressed opinions and
the social graph. Solved this
problem in a constrained
optimization framework
and design efficient
algorithms, which we
validate on both synthetic
and real-world Twitter
data.

3 Analysis A study on Twitter user-
follower network: a
network based analysis
Year:2013 3 Uncovered some of the
essential properties of the
complete Twitter user-
follower network. The
properties include degree
distribution, connectivity,
strength of following
relationships, clustering
coefficient
4 Influence,
data
mining
Key Opinion Leaders in
Recommendation
Systems: Opinion
Elicitation and Diffusion
Year: 2020 7 This paper investigates how
to develop a novel
recommendation system by
explicitly capturing the
influence from key opinion
leaders to the whole
community. Centering
around opinion elicitation
and diffusion, we propose
an end-to-end Graph-based
neural model - GoRec.
5. Influencers A Grounded Theory
Analysis of the
Techniques Used by
Social Media Influencers
and Their potential for
Influencing the Public
Regarding Environmental
Awareness
Year:2019 7 This study reports on a
grounded theory analysis
that explored the literature
related to the characteristics
of SMIs and the techniques
used by SMIs that could be
used by researchers for
influencing the public
regarding environmental
awareness and pro-
environmental behaviour.
6. Analysis,
social
network
Brand community
analysis on social
networks using graph
representation learning
Year:2019
Content:
Symposiu
m
8 Build a social network
graph, considering user
nodes and friendship
relations; then we compare
it with a heterogeneous
graph model, where also
posts and hash-tags are
considered as nodes and
connected to the different
node types; we finally build
also a reduced network,
generated by inducing
direct user-to-user
connections through the
intermediate nodes
7. Social
media,
social
network
Can We Trust Social
Media Data? Social
Network Manipulation by
an IoT Botnet
Year:2017 32 The paper explains how an
IoT botnet conducts social
network manipulation and
illustrates that the fraud is
driven by OSN users,
mainly entertainers, small
online shops and private
users.
8 Social
media
Mining social
media with social theories
: a survey
Year:2014 35 This article reviews some
key social theories in
mining social media, their
verification approaches,
interesting findings, and
state-of-the-art algorithms.

We also discuss some
future directions in this
active area of mining social
media with social theories.
9 Social
network
analysis
Social network analysis
and mining for business
applications
Year:2011 28 This article we use a
business process
classification framework to
put the research topics in a
business context and
provide an overview of
what we consider key
problems and techniques in
social network analysis and
mining from the perspective
of business applications.
10 Social
network
analysis
Encyclopedia of social
network analysis and
mining
Year:2014 41 Researchers and
practitioners will benefit
from a comprehensive
perspective on the
methodologies for analysis
of constructed networks,
and thedata mining and
machine learning
techniques that have proved
attractive for sophisticated
knowledge discovery in
complex applications. Also
addressed is the application
of social network
methodologies to other
domains, such as web
networks and biological
networks.
11 Social
media
network
Mining social networks
using heat diffusion
processes for marketing
candidates selection
Year:2008 55 This paper presents three
diffusion models, along
with three algorithms for
selecting the best
individuals to receive
marketing samples. These
approaches have the
following advantages to
best illustrate the properties
of real-world social
networks.
12 Social
network
analysis
Maximizing product
adoption in social
networks
Year:2012 96 This and other previous
papers tacitly assume that a
user who is influenced (or,
informed) about a product
necessarily adopts the
product and encourages her
friends to adopt it.
However, an influenced
user may not adopt the
product herself, and yet
form an opinion based on
the experiences of her
friends, and share this
opinion with others.

13 Social
media
influence
Maximizing influence in a
competitive social
network: a follower's
perspective
Year:2007 52 This paper propose two
models for the spread of
influence of competing
technologies through a
social network and consider
the influence maximization
problem from the follower's
perspective. In particular
we assume the follower has
a fixed budget available
that can be used to target a
subset of consumers and
show that, although it is
NP-hard to select the most
influential subset to target,
it is possible to give an
efficient algorithm that is
within 63% of optimal.
14 Social
networks
Optimal marketing
strategies over social
networks
Year:2013 67 This paper discusses the use
of social networks in
implementing viral
marketing strategies. While
influence maximization has
been studied in this context
(see Chapter 24 of [10]), we
study revenue
maximization, arguably, a
more natural objective. In
our model, a buyer's
decision to buy an item is
influenced by the set of
other buyers that own the
item and the price at which
the item is offered.
We focus on algorithmic
question of finding revenue
maximizing marketing
strategies.
15 Social
influence
Staticgreedy: solving the
scalability-accuracy
dilemma in influence
maximization
Year:2013 70 This paper focuses on
solving this scalability-
accuracy dilemma. We
point out that the essential
reason of the dilemma is the
surprising fact that the
submodularity, a key
requirement of the objective
function for a greedy
algorithm to approximate
the optimum, is not
guaranteed in all
conventional greedy
algorithms in the literature
of influence maximization.
16 Social
media
influence
Efficient influence
maximization in social
networks
Year:2009 55 This paper shows the
efficient influence
maximization from two
complementary directions.

17 Social
media
network
A fast approximation for
influence maximization in
large social networks
Year:2014 100 This paper deals with a
novel research work about a
new efficient
approximation algorithm
for influence maximization,
which was introduced to
maximize the benefit of
viral marketing.
18 Social
networks
Targeted influence
networks
Year:2016 100 This paper formalizes the
problem targeted influence
networks. We adopt a login
model where each user is
associated with a login
probability and he can be
influenced by his neighbors
only when he is online.
19 Social
media
analytics
Personalized influence
maximization on social
networks
Year:2013 100 In this paper, we study a
new problem on social
network influence
maximization. The problem
is defined as, given a target
user $w$, finding the top-k
most influential nodes for
the user.
20 Social
media
analytics
The power of social
media analytics
Year:2014 33 This study explores
how social media popularit
y necessitates use
of social-media analytics,
the underlying stages of the
analytics process.
Database Two: Science Direct
Number Keywords Title Filters Number
of
related
articles
Notes
1 Analysis,
social
networks
Tweeting the United
Nations Climate
Change Conference
in Paris (COP21):
An analysis of a
social network and
factors determining
the network
influence
Year:2020 18 First performed a network
analysis of the English
tweets during the first 10
days of the United Nations’
Conference of the Parties in
Paris in 2015. Based on a
quota sample of 133 Twitter
accounts and using both
manual and machine coding,
we further found that the
number of followers (but not
the size of following) and
the common-goal frame

(i.e., mitigation/adaptation)
positively predicted an
account's influence in the
Twitter network, whereas
the conflict frame negatively
predicted an
account's network influence.
2 Influence A trust model for
analysis of trust,
influence and their
relationship in social
network
communities
Year: 2019 34 This study proposes
a SNTrust model to find the
trust of nodes in a network
using a local and global trust
and also investigates trust,
influence and their
relationship in SN
communities. Different SN-
based influence evaluation
approaches named K-core,
closeness centrality,
eigenvector centrality, and
page rank is used to find
influential nodes.
3. Network
analysis
Examining
similarities in eating
pathology, negative
affect, and
perfectionism among
peers: A social
network analysis
Year: 2019 23 This study sought to
replicate findings
of homophily for eating
pathology using social
network analysis and to test
if similarity in eating
pathology is present above
and
beyond homophily for eating
disorder risk factors and
correlates
4. Analysis,
social
networks
Factors Influencing
Social Networks Use
for Business: Twitter
and YouTube
Analysis
Year:2017 27 The authors test eight items
for the social networks
Twitter and YouTube that
even though are not so used
by Romanian companies,
they have proven to
influence the online
performance of the business
in various sectors with at
least 30%
5. Analysis,
social
networks
Characterizing
Instructional Leader
Interactions in a
Social Learning
Management System
using Social
Network Analysis
Year:2019 28 Contribution of this study is
on the the method to verify
the instructional leadership
of administrators in its
inclusion in the
implementation of sLMS.
6. Network
analysis
How leader role
identity influences
the process of leader
emergence: A social
network analysis
Year:2018 126 Proposed a social network-
based process model
whereby leader role identity
predicts network centrality
(i.e., betweenness and
indegree), which then
contributes to leader
emergence.
7. Analysis Diffusion pattern
analysis for social
Year:2015 16 The present study aimed,
first, to find key SNS

networking sites
using small-world
network multiple
influence model
characteristics that can be
directly related to their
diffusion patterns; second, to
classify existing SNSs
according to those derived
characteristics, and finally,
to examine whether the
different types of SNS
actually lead to distinct
diffusion patterns or not.
8. Network
analysis
Semantically
enhanced network
analysis for
influencer
identification in
online social
networks
Year:2019 91 Proposed the use of
semantic analysis to filter
out such kind of interactions,
achieving a simplified graph
representation that preserves
the main features of the
OSN, allowing the detection
of true influencers.
9 Social
media
Social media
data for
conservation science:
A methodological
overview
Year:2019 49 This paper describes
available sources of social
media data and approaches
to mining and analysing
these data for conservation
science.
10 Data
mining,
social media
Data mining techniques in social
media: A survey
Year:2016 23 The goal of this study is
to analyze the data mining
techniques that were
utilized by social media
networks between 2003
and 2015.
11 Big data
analytics
Big data analytics meets social
media: A systematic review
of techniques, open issues, and
future directions
Year:2021 44 This paper demonstrate
how big data analytics
meets social media, and a
comprehensive review is
provided on big data
analytic approaches in
social networks to search
published studies between
2013 and August 2020,
with 74 identified papers.
12 Social
media
Social media big data analytics:
A survey
Year:2019 41 This study compares
possible big data analytics
techniques and their
quality attributes.
13 Big data,
Social
media
network
Research on Big Data–A
systematic mapping study
Year:2017 66 The aim of this paper is to
examine how do
researchers grasp the big
data concept.
14 Social
media
information
Business intelligence model to
analyze social
media information
Year:2018 35 The purpose of this
research, to create a
business intelligence
dashboard to observe the
performance of each
Topic or channel of news
posted to social media
accounts such as
Facebook and Twitter.

15 Social
media
analytics
Social media data analytics for
business decision making
system to competitive analysis
Year:2022 27 Due to content saturation,
social media's true
meaning regarding
business data is hardly
ever found. Therefore, in
this paper, the business
decision making system
(BDMS) has been
proposed to
develop business using
social media data
analytics. BDMS provides
a clear understanding of
the key principles, issues
and functionality, and big
social data developments
16 Social
media
analytics
Big data-assisted social media
analytics for business model for
business decision making
system competitive analysis
Year:2022 25 In this paper, Big Data-
assisted Social Media
Analytics for Business
(BD-SMAB) Model
increases awareness and
affects decision-makers in
marketing strategies.
Companies can use big
data analytics in many
ways to enhance
management. It can
evaluate its competitors in
real-time and change
prices, make deals better
than its competitors' sales,
analyze competitors'
unfavorable feedback and
see if they can outperform
that competitor.
17 Social
media
analytics
Social media analytics and
business intelligence research:
A systematic review
Year:2020 66 This study compared
social media data with the
other open data (e.g., gray
literature, public
government data) in terms
of data content,
collection, updatability
and structure, which are
determined through a
thorough discussion with
experts. Next, this study
selected 57 social media-
based BI research articles
from the Web of Science
(WoS) database and
analyzed them with three
research questions about
the data, methodologies,
and results to understand
this research domain.
18 Social
media
analytics
Social media analytics for
enterprises: Typology, methods,
and processes
Year:2018 36 This article presents a
simple typology of social
media analytics for
enterprises. It also
discusses various

analytics methods for
social media data. Then,
this article discusses
management processes of
social media analytics for
enterprises. An
illustration of social
media analytics is
provided with real-world
consumer review data.
19 Social
media
analytics
Business social media analytics:
Characterization and conceptual
framework
Year:2018 57 This paper presents a
definition that subsumes
salient aspects of existing
characterizations and
incorporates novel
features of interest to
Business SMA. Further,
we examine available
conceptual frameworks
for Business SMA and
advance a framework that
comprehensively models
the Business SMA
phenomenon. We also
conduct a survey of
recently published SMA
research in the premier,
academic Management
Information
Systems journals and use
some of the surveyed
papers to validate our
framework.
20 Social
media
analytics
Social media analytics: An
interdisciplinary approach and
its implications for information
systems
Year:2014 69 This paper introduces
social media analytics
(SMA) as an emerging
interdisciplinary research
field that, in our view,
will have a significant
impact on social media-
related future research
from across different
academic disciplines.
Database Three: Springer

Number Keywords Title Filters Number
of related
articles
notes
1 Influence In the search of
quality influence on
a small scale–micro-
influencers discovery
Year: 2018
Content:
Conference
paper
100 A new concept of
micro-influencers in
the context of Social
Network Analysis,
define the notion and
present a flexible
method aiming to
discover them. The
approach is tested on
two real-world
datasets of Facebook
and Pinterest
2 Analysis Enhance sentiment
analysis on social
networks with social
influence analytics
Year:2019-
2020
9 Utilized
heterogeneous graphs
to infer sentiment
polarities at user-
level. We show that
information about
social influence
processes can be
used to improve
sentiment analysis.
3. Social
networks
Identifying Peer
Influence in Online
Social Networks
Using Transfer
Entropy
Year: 2013
Content:
Conference
paper
3 Introduced a model
free approach to
formulate causal
inferences of
behaviors among
user peers.
Experimental results
show that influence
measured by our
approach could
successfully
reconstruct the
underlying networks
structure.
4 Social media User profiling for big
social media data
using standing
ovation model
Year:2018 21 aimed to develop an
integrative solution
entailing a
combination of these
methodological
advances within a
single framework
that could facilitate
attribution and
differentiate OSN
members.
5. Influence,
social
network
Exploring
Interactions in Social
Networks for
Influence Discovery
Year:2019
Content:
Conference
paper
6 Proposed a flexible
method that
considers type,
quality, quantity and
time of reactions and,
as a result, the
method assesses the
influence
dependencies within
the social network.

6. Influence Effective and
efficient location
influence mining in
location-based social
networks
Year: 2018 6 Introduced a notion
of location
influence that
captures the ability of
a set of locations to
reach
out geographically by
utilizing their visitors
as message carriers.
7 Data science Data science and
analytics: an
overview from data-
driven smart
computing, decision-
making and
applications
perspective
comprehensive view
on “Data Science”
including various
types of advanced
analytics methods
that can be applied to
enhance the
intelligence and
capabilities of an
application through
smart decision-
making in different
scenarios.
8 Social media
analytics
Big data & analytics
for societal impact:
Recent research and
trends
Year: 2018 100 This paper proposes
a simple framework
to understand the
research on big data
applications for
societal impact The
three concentric
circles represent the
a) data and the
infrastructure, b)
techniques for big
data analysis and
interpretation, and c)
application domains.
9 Natural
language,
social media
Natural language
processing for social
media
Year:2015 28 This study reviews
the existing
evaluation metrics
for NLP and social
media applications,
and the new efforts in
evaluation campaigns
or shared tasks on
new datasets
collected from social
media. Such tasks are
organized by the
Association for
Computational
Linguistics (such as
SemEval tasks) or by
the National Institute
of Standards and
Technology via the
Text REtrieval
Conference (TREC)
and the Text

Analysis Conference
(TAC).
10 Data science
and social
media
Supervised and
unsupervised
learning for data
science
Year:2019 94 This study Features
applications from
healthcare,
engineering, and
text/social media
mining that exploit
techniques from
semi-supervised and
unsupervised
learning.
11 Data science Mobile data
science and
intelligent apps:
concepts, AI-based
modeling and
research directions
Year:2021 29
This paper presents
a comprehensive
view on “mobile data
science
and intelligent
apps” in terms
of concepts and AI-
based
modeling that can be
used to design and
develop intelligent
mobile applications
for the betterment of
human life in their
diverse day-to-day
situation. This study
also includes the
concepts and insights
of various AI-
powered intelligent
apps in several
application domains,
12 Social media
network
The dynamics of
health behavior
sentiments on a large
online social network
Year: 2013 100 This paper finds the
effects of
neighborhood size
and exposure
intensity are
qualitatively very
different depending
on the type of
sentiment. Generally,
we find that larger
numbers of
opinionated
neighbors inhibit the
expression of
sentiments. We also
find that exposure to
negative sentiment is
contagious - by
which we merely
mean predictive of
future negative
sentiment expression
- while exposure to

positive sentiments is
generally not.
13 Social media Us and them:
identifying cyber
hate on Twitter
across multiple
protected
characteristics
Year:2016 86 This paper focuses
on building a data-
driven blended model
of cyber hate to
improve
classification where
more than one
protected
characteristic may be
attacked (e.g. race
and sexual
orientation),
contributing to the
nascent study of
intersectionality in
hate crime.
14 Social media
networks
How to measure
influence in social
networks?
discussion on these
metrics, algorithms,
and models. This
work helps
researchers to
quickly gain a broad
perspective on
metrics, algorithms,
and models for
influence in social
networks and their
relative potentialities
and limitations.
15 Social
network
analysis
An empirical
comparison of
influence
measurements for
social network
analysis
Year:2016 100 This paper focuses
on the problem of
predicting influential
users on social
networks. We
introduce a three-
level hierarchy that
classifies the
influence
measurements. The
hierarchy categorizes
the influence
measurements by
three folds, i.e.,
models, types and
algorithms.
16 Social media
influence
Social Influence
Analysis in Online
Social Networks for
Viral Marketing: A
Survey
Year:2022 100 Methods for
influence modeling,
maximization, and
identifying
influential nodes are
discussed in this
paper. Using cutting-
edge research on
viral marketing’s
impact on social
influence, we hope to
serve as a resource

for aspiring
researchers.
17 Social media
networks
Systematic literature
review on identifying
influencers in social
networks
Year:2023 100 This paper review s
the definitions of
influencers, the
datasets used for
evaluation purposes,
the methods of
identifying
influencers, and the
evaluation
techniques.
Furthermore, the
quality assessment of
the recently
published papers also
has been performed
in different aspects to
find whether research
about identifying
influencers has
progressed.
18 Social media Identification of best
social media
influencers using
ICIRS model
Year:2023 100 This paper proposes
a new model where
an active promoter
may lose his
influencing potential
over time, go to a
recovered state where
he is no longer active
or can activate
others, and then go to
a susceptible state
where he is prone to
getting influenced in
the future.
19 Data science Identification of top-
k influential nodes
based on discrete
crow search
algorithm
optimization for
influence
maximization
Year:2021 100 In this study, in order
to solve the influence
maximization
problem more
effectively, a meta-
heuristic discrete
crow search
algorithm (DCSA)
using the intelligence
of crow population is
proposed.
20 Social
networks
A clique-based
discrete bat
algorithm for
influence
maximization in
identifying top-k
influential nodes of
social networks
Year:2021 100 The proposed
algorithm is based on
the clique partition of
a network and
enhances the initial
DBA algorithm's
stability. The
experimental results
show that the
proposed clique-
DBA algorithm
converges to a
determined local

influence estimation
(LIE) value in each
run, eliminating the
phenomenon of large
fluctuation of LIE
fitness value
generated by the
original DBA
algorithm.
3. Selection Criteria
During the process of literature search, it was a great challenge to review all relevant prior
research and thus we conducted review for only selected research papers. But reviewing
selected studies generated the risk of overseeing few of significant research. Thus, our major
focus was only to recognize the main concerns and identify persuasive research on the title of
study. Regarding selection of research papers, we conducted a citation frequency investigation
to regulate which research should be included and circulate the basis of purpose statement. The
reference indexes of ACM Digital library demonstrated a wide image on which researchers and
studies were often referenced by different authors and thus graded based on their indexing
frequency. It was observed that Science Direct possessed more reference index in contrasts to
Springer and ACM Digital library, as in whole Science Direct has referenced more research
papers and different types of publication in comparison to other databases. There is numerous
research which offered outstanding outlines of the issues related to the usage of ISI web
information as a dataset described in a prior research (Harzing and van der Wal, 2008).
Subsequently the search consequences obtained from different database sources a cluster of
inclusion and exclusion conditions were applied to facilitate in the recognition of related
primary research. Thus, inclusion condition is utilized to choose primary research which shows
relevant data analysis procedure, determination and interaction between followers and
influences in social media network. Whereas for exclusion condition they are utilized to
eradicate primary research which do not focuses on main title researched in the above
background context, are unavailable and directly relevant to an existing research of the similar
researcher.
Inclusion Condition:
 Research which shows similarity in at least one of the researched terms.
 Research that possesses best practices forms.
 Studies that are relevant to social media networks relevant to data science.
 Studies that are relevant to the concept of effect in social media network.
 Studies which are relevant to research queries.
Exclusion Condition

 Research which does not shows similarity in at least one of the researched terms.
 Research that does not possess best practices forms.
 Studies which are published prior to 31.12.1999.
 Studies that are not relevant to the concept of effect in social media network.
 Studies which are not relevant to research queries.
Title Included/Excluded Database Reason
In the search of quality
influence on a small scale–
micro-influencers discovery
 Springer A new concept of micro-influencers in the
context of Social Network Analysis, define
the notion and present a flexible method
aiming to discover them. The approach is
tested on two real-world datasets of Facebook
and Pinterest
Enhance sentiment analysis on
social networks with social
influence analytics
× Springer Very broad, not likely going to be benefit to
the research
Identifying Peer Influence in
Online Social Networks Using
Transfer Entropy
× Springer Could be on benefit, but better articles are
below that have more relevant industry
standard information.
User profiling for big social
media data using standing
ovation model
× Springer Related to the subject however
the proposed solution not
relevant to the topic.
Effective and efficient
location influence mining in
location-based social networks
× Springer The paper is not relevant to the
research topic.
Data science and analytics: an
overview from data-driven
smart computing, decision-
making and applications
perspective
the research
Big data & analytics for
societal impact: Recent
research and trends
Natural language processing
for social media
research topic.
Supervised and unsupervised
learning for data science
Mobile data science and
intelligent apps: concepts, AI-
based modeling and research
directions
the research
The dynamics of health
behavior sentiments on a large
research topic.

Us and them: identifying
cyber hate on Twitter across
multiple protected
characteristics
How to measure influence in
social networks?
the research
An empirical comparison of
influence measurements for
social network analysis
× Springer No primary research conducted
in the study.
Social Influence Analysis in
Online Social Networks for
Viral Marketing: A Survey
Systematic literature review
on identifying influencers in
social networks
research topic.
Identification of best social
media influencers using ICIRS
model
research topic.
Identification of top-
k influential nodes based on
discrete crow search algorithm
optimization for influence
maximization
A clique-based discrete bat
algorithm for influence
maximization in identifying
top-k influential nodes of
social networks
 Science
direct
Proposed a social network-based process
model whereby leader role identity predicts
network centrality (i.e., betweenness and
indegree), which then contributes to leader
emergence.
Mobile data science and
intelligent apps: concepts, AI-
based modeling and research
directions
 Springer This research proposed a flexible method that
considers type, quality, quantity and time of
reactions and, as a result, the method assesses
the influence dependencies within the social
network.
The dynamics of health
behavior sentiments on a large
 Springer The researcher introduced a notion of location
influence that captures the ability of a set of
locations to reach out geographically by
utilizing their visitors as message carriers.
Us and them: identifying
cyber hate on Twitter across
multiple protected
characteristics
 Science
direct
Very useful for cross referencing information.
Fore worded by original author, whom has a
useful amount of information in field.
How to measure influence in
social networks?
 Science
direct
Outstanding details, with good evaluation on
network analysis for influencers
An empirical comparison of
influence measurements for
social network analysis
 Science
direct
Very detailed, useful information.
Social Influence Analysis in
Online Social Networks for
Viral Marketing: A Survey
 Science
direct
Very useful, specific to the industry and
questions raised

Systematic literature review
on identifying influencers in
social networks
 Science
direct
The paper is relevant to the aim
of the research using data mining technique.
Identification of best social
media influencers using ICIRS
model
 Science
direct
The goal of this study is to analyze the data
mining techniques that were utilized by social
media networks between 2003 and 2015.
Identification of top-
k influential nodes based on
discrete crow search algorithm
optimization for influence
maximization
 Science
direct
The purpose of this research, to create a
business intelligence dashboard to observe the
performance of each Topic or channel of news
posted to social media accounts such as
Facebook and Twitter.
A clique-based discrete bat
algorithm for influence
maximization in identifying
top-k influential nodes of
social networks
 Science
direct
It shows the the business decision making
system (BDMS) has been proposed to
develop business using social media data
analytics. BDMS provides a clear
understanding of the key principles, issues and
functionality, and big social data
developments.
Social media analytics: An
interdisciplinary approach and
its implications for
information systems
 Science
direct
It provides a significant impact on social
media-related future research from across
different academic disciplines.
Tweeting the United Nations
Climate Change Conference in
Paris (COP21): An analysis of
a social network and factors
determining the network
influence
× Science
direct
Could be on benefit, but better articles are
A trust model for analysis of
trust, influence and their
relationship in social network
communities
× Science
direct
Very broad, not likely going to be benefit to
the research
Examining similarities in
eating pathology, negative
affect, and perfectionism
among peers: A social
network analysis
× Science
direct
No primary research conducted
in the study.
Factors Influencing Social
Networks Use for Business:
Twitter and YouTube
Analysis
× Science
direct
Characterizing Instructional
Leader Interactions in a Social
Learning Management System
using Social Network
Analysis
× Science
direct
Related to the subject however
Social media data for
conservation science: A
methodological overview
× Science
direct
standard information for

Big data analytics meets social
media: A systematic review
of techniques, open issues, and
future directions
× Science
direct
No primary research conducted
in the study.
Social media big data
analytics: A survey
× Science
direct
the research
Research on Big Data–A
systematic mapping study
× Science
direct
The paper is not relevant to the
research topic.
Big data-assisted social media
analytics for business model
for business decision making
system competitive analysis
× Science
direct
Social media analytics and
business intelligence research:
A systematic review
× Science
direct
The paper is not relevant to the
research topic.
Social media analytics for
enterprises: Typology,
methods, and processes
× Science
direct
the research
Cross-platform Interactions
and Popularity in the Live-
streaming Community
× Science
direct
Role of conformity in opinion
dynamics in social networks
× ACM Very broad, not likely going to be benefit to
the research
A study on Twitter user-
follower network: a network
based analysis
× ACM Could be on benefit, but better articles are
Can We Trust Social Media
Data? Social Network
Manipulation by an IoT
Botnet
Mining social
media with social theories: a
survey
× ACM Related to the subject however
Social network analysis and
mining for business
applications
standard information for
Encyclopedia of social
network analysis and mining
the research
Mining social networks using
heat diffusion processes for
marketing candidates selection
Maximizing product adoption
in social networks

Maximizing influence in a
competitive social network: a
follower's perspective
× ACM No primary research conducted
in the study.
Optimal marketing strategies
over social networks
Staticgreedy: solving the
scalability-accuracy dilemma
in influence maximization
the research
Efficient influence
networks
 ACM This paper shows the efficient influence
maximization from two complementary
directions.
A fast approximation for
influence maximization in
large social networks
× ACM No primary research conducted
in the study.
Targeted influence
networks
Personalized influence
maximization on social
networks
The power of social
media analytics
 ACM Explores how social media popularity
necessitates use of social-media analytics, the
underlying stages of the analytics process.
4. Conclusion
The existing literature search report pursued to constitute in the recognition of end-users
relevant to data science analytics procedures along with to show the main purpose of analysis
and the areas that were highly impacted by the influence of social media networks. This report
entailed literature reviews published between 2000 to 2020 era. The outcomes of the review
were four data representation models, ten data analytics procedure and six major perspectives
behind social media networks relevant to data analytics and around twenty area were observed.
The selected research papers demonstrated that Graphs are regarded as the most utilized
procedure for data representation model. 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. The major
objective of this study was to investigate different primary researches relevant to role of data
science is social media networks the given research queries were generated. 1. Which
procedures have been cast-off to investigate users associated data in social media? 2. What is

the aim of investigating users associated data in social media?3. How is it probable to practise
investigating methods while considering interactions between followers and influencers?
The main perspective was to analyze the interaction and user’s coordination. The topmost
inter-related areas with social media networks found were Computer Science, Business and
Sociology. For future study, it is recommended to generate a data mining strategy to find the
interaction between users and influences with the help of Graph. Moreover, graph matching
and transformation procedures can also be implemented on the interaction framework utilizing
Graph Matching and Transformation Engine (GMTE) for analysis.
Although, the research was cautiously performed but we have to confess few limitations.
Because of huge number of studies, it was not probable to sought the whole literature. The list
of research papers in this sector is not a complete list. Additionally, due to increment in the
number of studies, research in same area may be in process. Another major limitation is that
some research papers and articles were not directly accessible through internet. Consequently,
the influence of social media networks and the usage of data science for data analytics are
evolving interdisciplinary study disciplines. Area of research such as data security and
protection, legal challenges and ethics can be determined and studied under numerous aspects
in the upcoming years.

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