social networking individual vs. crowd behavior (connected intelligence)

International Journal of Advanced Engineering, Management and Science (IJAEMS) [Vol-2, Issue-12, Dec.- 2016]
Infogain Publication (Infogainpublication.com) ISSN : 2454-1311
www.ijaems.com Page | 2004
Social Networking Individual vs. Crowd Behavior
(Connected Intelligence)
Ubaid Ur RehmanRahimi, Shuaib Ibrahim Adam Akoush
Dept. Telecommunication and Information Engineering, Nanjing University of Posts & Telecommunications, No. 9,
Wenyuan Road, Nanjing (210046) Tel: +86 13962524174
Abstract— The study of Human behavior is much more
complicated in various situations, especially on the
spectrum of Social Networks. The study of individual
behavior cannot be replicated for a group/crowd behavior
which can have many social and behavioral dimensions. In
the connected world where intelligence is shared among
individuals and groups, there exists another kind of
complexity which needs to be examined.The complexity of
human behaviors as an individual or as a group on the
social networks is much more versatile and erratic. The
research work studies and analyzes these behaviors in a
connected networked intelligent environment and as to how
these behaviors are reflected towards Connected
Intelligence. Consequently it defines how they can affect the
intelligent analytical outcomes. Finally it comes up with a
generic model which can be applied in any setup.
Keywords— Knowledge management, connected
Intelligence, individual Behavior, crowd behavior, social
networks.
I. INTRODUCTION/BACKGROUND
The study of Human behavior is much more complicated in
various situations, especially on the spectrum of Social
Networks. The study of individual behavior cannot be
replicated for a group/crowd behavior which can have many
social and behavioral dimensions. If we look at the birds,
when they fly in a group formation, they follow a certain
specific synchronized behavior pattern. Human beings are
not that easy to predict in a social environment. Let’s first
have a look at the individual and crowd behavior’s and does
their comparative analysis.
- Individual Behavior
The way an individual addresses a situations is influenced
by many factors. Some of the key factors which influence
an individual’s attitude can be summarized as;
• Abilities
• Gender
• Race and culture
• Attribution
• Perception
• Attitude
Abilities are the traits a person learns from the
environment around as well as the traits a person is gifted
with by birth. These traits can be intellectual abilities,
physical abilities or self-awareness abilities. Similarly
behavioral changes also tend to be different for different
genders. Race & Culture are two entities in which the race
involves a group of people sharing similar physical
features. Culture on the other hand is defined as the traits,
ideas, customs and traditions one follows. Both race and
culture have great influence in the society. This is
followed byperception which is an intellectual process of
interpreting something that we see or hear in our mind and
use it later to judge or give a verdict. And finally we have
attitude is the learnt reaction of a person over a time span.
All the above factors contribute to the way we behave. We
generally never go into the details about these factors but
they are responsible for whatever we do in life.Similarly
when these individuals are put into organizations where
they have to work in crowded environment’s as a team,
various others factors come into play which include
personal factors, age, gender, religion, marital Status,
experience, intelligence, ability, perception, attitude and
values.
- Crowd Behavior
Crowd behavior is the behavior that is conducted by
individuals in a gathering of people who share a purpose.
They have shown that behavior in crowds is far more
mindful, rational and socially organized. Crowd
psychology, also known as mob psychology, is a branch
of social psychology. Social psychologists have developed
several theories for explaining the ways in which
the psychology of a crowd differs from and interacts with
that of the individuals within it.

Many theories have been propounded by various
psychologists and sociologists to explain why the crowd
behaves in a particular way. Some of them are;
• Le Bon’s Theory[1]
• McDougall’s Theory[2]
• Freud’s Theory[3]
• Allport’s Theory[4]
• Turner’s Theory[5]
Crowd or collectivebehavior isthe kinds of activities
engaged in by sizable but loosely organized groups of
people. Crowd behavior is guided by unique social norms,
which are established by members of the crowd. In short, it
is a combination of like-minded individuals, anonymity,
and shared emotion that leads to crowd behavior.
We have looked at the individual and the crowd behavior
separately. However the insight that individuals in a crowd
generate behavior as opposed to the group is the core of
modern theories. It takes special dimension when we
encounter the social networks and how they depict an
individual’s behavior in a connected environment of
connected crowd behavior. With the availability of social
network data, it has become possible to relate the behavior
of individuals to that of their acquaintances on a large scale.
Social Media
Over the years the social media has brought about a
revolution in the lives of individuals and groups/crowds in
the way they conduct their lives.
Within a few years social media has become an integral part
of the world. Especially young people cannot think of
communication without thinking of online-networks like
Facebook, Google+, and Twitter. If we simply look at the
Facebook, the largest and the most active social media
application, the statistics are mind blowing. As of the third
quarter of 2016, Facebook had 1.79 billion monthly active
users. 823M of those are mobile-only users. There are 1.083
billion daily active users out of which 47% of Facebook
users only access the platform through mobile. 83% of
parents on Facebook are friends with their children.
Facebook adds 500,000 new users every day; 6 new profiles
every second. Worldwide, 38.6% of the online population
use Facebook. The average (mean) number of friends is
338, and the median (midpoint) number of friends is 200.
Users spend an average of 20 minutes per day on the site
with 4 million likes every minute More than 250 billion
photos have been uploaded to Facebook which equates to
350 million photos per day [6].
These are just some of the statistics. It is now important for
us to study the impact of social media on individuals and
groups. Social networks have removed all the
communication and interaction barriers, and now one can
communicate his/her perception and thoughts over a variety
of topics. Crowds are able to share and communicate with
like-minded people and can ask for the input and opinion on
a particular topic. Instead of individual thinking, now we
are moving towards a knowledge core which is the result of
social media and the connected intelligence achieved
through the interconnection of networks. One of the impact
of social networking sites is that it has united people on a
huge platform for the achievement of some specific
objective. This is very important to bring the change in a
society.As humans tend to bow to peer pressure in real life
and as well in social media, social media influences their
ability to think independently. People seem to be more open
to peer pressure within social networks.
Having said that, the long term effects of the social media
revolution are not known yet neither on the society as a
whole nor on the individuals. Therefore, a thorough
reflection is indispensable. Since the effect of social media
is subtle and develops over time.
One of the major component of social media’s development
is certainly the connected intelligence. All the
communication takes place on the digital interconnected
networks, thus possessing in its millions of servers the
connected intelligence needed to visualize the crowd and
individual behaviors.
Connected Intelligence
Connected Intelligence deals with the consequences of
massive global networking and what it can lead to when it
reaches a critical mass of "connected intelligence." Will the
sum total of people's connected intelligence will be more
intelligent than any one person's intelligence, is one
question which stirs our mind. This leads to the possibility
that we are undergoing one of the greatest insights into the
evolution of our species. Connected intelligence may be the
next step in the evolution of human intelligence. The
evolution of connected intelligence is presented below;
Fig.1: Evolution of Connected Intelligence
MIT acknowledged the importance of connected
intelligence in October 2006, when it launched the Center

International Journal of Advanced Engineering, Management and
Infogain Publication (Infogainpublication.com
www.ijaems.com
for Collective Intelligence lead by “Future of Work”
author Tom Malone. Its goal was to understand h
harness the power of large numbers of people connected
together through Internet and other technologies to better
solve a range of business, scientific, and societal problems.
The burning question which is explored here concerns how
to integrate individual and collective concerns in user
centered environments. More importantly, what are
personalization and recommendation mechanisms that exist
for collectives, individuals and crowds in communities?
This eventually leads to virtual communities that sha
acquire individual and collective knowledge.
Through connected intelligence, data scientists extract
relevant information from social channels and integrate it
with additional data to get insight into individual and crowd
behavior patterns. This allows them to go beyond social
media listening; giving people the full context and a strong
foundation on which to base knowledge driven paradigms.
II. RESEARCH METHODOLOGY
Our research methodology is descriptive in nature. Once
gone through the Individual and crowd behavior, we need to
develop a model which will integrate the two into connected
intelligence thus giving an output for the knowledge
management tool.
Model Development
Having looked at various dimensions of the human
behaviors, now we are in a position to design a sustainable
Model.
Fig.2: Designed Model
The designed model has the following five
segments/components.
- Individual Behavior
- Crowd Behavior
- Group Influence/Behavior
- Collective Intelligence
- Knowledge Management
International Journal of Advanced Engineering, Management and Science (IJAEMS)
Infogainpublication.com)
for Collective Intelligence lead by “Future of Work” [7]
author Tom Malone. Its goal was to understand how to
harness the power of large numbers of people connected
together through Internet and other technologies to better
solve a range of business, scientific, and societal problems.
The burning question which is explored here concerns how
ividual and collective concerns in user
centered environments. More importantly, what are
personalization and recommendation mechanisms that exist
for collectives, individuals and crowds in communities?
This eventually leads to virtual communities that share and
acquire individual and collective knowledge.
Through connected intelligence, data scientists extract
relevant information from social channels and integrate it
with additional data to get insight into individual and crowd
lows them to go beyond social
media listening; giving people the full context and a strong
foundation on which to base knowledge driven paradigms.
RESEARCH METHODOLOGY
Our research methodology is descriptive in nature. Once
gone through the Individual and crowd behavior, we need to
develop a model which will integrate the two into connected
intelligence thus giving an output for the knowledge
Having looked at various dimensions of the human
behaviors, now we are in a position to design a sustainable
The designed model has the following five
The Individual model comprises of the following inputs;
- Values
- Personality
- Emotions
- Attitudes
- Stress
These create the respective motivation and ability. The role
perceptions and the situatio
role in developing the individual behavior and the outcome
in the form of results.
Similarly the group influence and the crowd behavior
impact the collective intelligence which comprises of
coordination and cognition. When al
the strong knowledge management/sharing mechanisms.
Let’s have a look at the individual components of the
designed model.
Fig.3: Individual Behavior
The individual behavior model
model that seeks to elaborate individual behavior as a result
of internal and external factors or influences combined
together. It consists of the following attributes of
individuality;
- Motivation
- Abilities
- Role Perception
- Situational Factors.
This model puts forward the concept that
have a mixed effect on individual
weakens, behavior will be affected
Fig.4: Group Influence
[Vol-2, Issue-12, Dec.- 2016]
ISSN : 2454-1311
Page | 2006
The Individual model comprises of the following inputs;
These create the respective motivation and ability. The role
perceptions and the situational factors play an important
role in developing the individual behavior and the outcome
Similarly the group influence and the crowd behavior
impact the collective intelligence which comprises of
coordination and cognition. When all combined, it leads to
the strong knowledge management/sharing mechanisms.
Let’s have a look at the individual components of the
Individual Behavior Model
The individual behavior model of individual behavior is a
model that seeks to elaborate individual behavior as a result
of internal and external factors or influences combined
It consists of the following attributes of
Situational Factors.
puts forward the concept that these four factors
have a mixed effect on individual behavior. If any factor
be affected.
4: Group Influence/Behavior Model

Here we see the external conditions imposed on the group.
The group is affected by the overall strategy, authority
structures, formal regulations, resources, performance
management system and the organizational culture. Group
member resources pertain to task- relevant and intellectual
abilities of individual members. In the group structure the
structural variables include roles, norms, status and the size
of the group. Group process is centered towards
communications, decision making, leadership and conflict.
Group tasks include standardized complex and simple tasks.
Fig.5: Connected Intelligence Model
Collective intelligence model depicts is shared or group
intelligence that emerges from thecollaboration, collective
efforts, and competition of many individuals and appears in
consensus decision making.
Fig.6: Knowledge Management
This Knowledge Management Model attempts offers a more
an overview of the knowledge management process. The
following three broad categories overlap and interact with
one another.
- Knowledge creation and Sensing
- Knowledge sharing and dissemination
- Knowledge organizing and capture
It also shows that which of the three categories are more
people oriented; and which are more, technology focused.
The last fundamental design model is the integration of the
models shown from Fig-3 to Fig-6, this coming up with an
integrated approach as shown in the designed model (Fig-
2).
III. CONCLUSION
The study of Human behavior, Social Networks and
Connected Intelligence have shown a lot of bonding in
relation to the individual and crowd behaviors. This area of
research has been neglected for a long time. In our
connected world intelligence is shared among individuals
and groups which brings in a lot of complexities which
needs to be addressed. More importantly there is a need to
come up with a modelling approach so as to implement it in
a social media setting where connected networks provide
connected intelligence which becomes an input to the
knowledge management.
REFERENCES
[1] Communication theory by communication
organization.
http://communicationtheory.org/contagion-theory/
[2] “Instinct Theory of Motivation”. The psychology
Notes by Alexandra.
[3] “Sigmund Freud” by Saul McLeod published 2013
[4] Boundless. “Allport's, Cattell's, and Eysenck's Trait
Theories of Personality.” Boundless Psychology.
Boundless, 20 Sep. 2016. Retrieved 24 Nov. 2016
[5] Turner's Theory of Social Evolution Rudolf Freund
Agricultural HistoryVol. 19, No. 2 (Apr., 1945), pp.
78-87
[6] “Facebook statistics directory”
[7] “Understanding Connected Intelligence”. Center for
Collective Intelligence (CCI). “Future of Work”
author Tom Malone (2004).

social networking individual vs. crowd behavior (connected intelligence)

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social networking individual vs. crowd behavior (connected intelligence)