Description of the Networked Individualistic Tendency Level of

Young Adults in Jabodetabek

Arsyan Makarim Sugiri

, Raymond Godwin

Psychology Department, Faculty of Humanities, Bina Nusantara University, Jakarta, 11480 Indonesia

Keyword: Networked Individualistic, Tedency Level, Young Adults

Abstract: Development of information and communication technology has created dramatic changes for society and

individuals. The biggest impact people can obtain includes facilitation to communicate without barriers of

time and space. This facility opens oppurtunities for individuals to connect and to create social relationships

with anyone. This opportunity, on the other side, may reduce individual’semphasize on their small groups

such as families or communities, which generally allow more direct face to face interaction. The

phenomena of this decreasing emphasize is called networked individualism. A person who is highly

networked individualisticmanages his/her social network based on their own needs and motivation, which is

established through various communication channels. This study aims to view description of the networked

individualism level of young adults in Jabodetabek, based on variations of the network structure and

interaction patterns. Based from the analysis, it was revealed that the level of the networked individualistic

tendency of young adults is largerlygoverned by its interaction or contact patterns.

1 INTRODUCTION

Technology has assisted human with such various

facilitites that people has begun to integrate it into

their daily life. Not only does technology help

workers, but it also assists people to meet their needs

of information, their business and socialization. The

presence of technology facilitates us to access

various kinds of information and to make direct

communication so that building and maintaining

relationship today has been easier than in the era of

the previous generation. Because of technology, the

way humans interact in this era has started to change

compared to their predecessor.

As a social creature, humans interact each other

through various channels, either verbal or non-

verbal. The interaction results in a social relationship

between two individuals which is called social

network. According to Christakis and Fowler

(Christakis and Fowler, 2009), humans deliberately

construct their own social network, in which they

associate themselves with people who have

something in common. Social network is very

similar to a group, which is a collection of

individuals who share common characteristics and

features. However, social network is more

specificlydirected towards person-to-person

relationships within the group (Christakis and

Fowler, 2009). The argument denotes that social

network focuses more on the personal relationship

between individuals than individuals’ relations to the

group as merely a collection of individuals with

similar traits and characteristics without considering

a person-to-person relationship within it.

Because access to technology facilitates us to

communicate either through short messages or video

calling, people’s social lives is getting easier and

people are completely autonomusto select social

bond (Rainie and Wellman, 2012). Furthermore,

Rainie and Wellman (2012) have suggested that this

may decline individuals’ limitations and emphasize

on small groups such families, community groups

and so forth. This decreasing emphasizes and group

limitations leads individuals to have more autonomy

to create social bonds based on their preference, and

such phenomenon is called networked individualism

(Rainie and Wellman, 2012).

1.1 Networked Individualism

Networked individualism refers to a social operating

system, characterized by decreasing individuals’

limitations and emphasizes on small group such as

Sugiri, A. and Godwin, R.

Description of the Networked Individualistic Tendency Level of Young Adults in Jabodetabek.

DOI: 10.5220/0010000400002917

In Proceedings of the 3rd International Conference on Social Sciences, Laws, Arts and Humanities (BINUS-JIC 2018), pages 75-80

ISBN: 978-989-758-515-9

 2022 by SCITEPRESS – Science and Technology Publications, Lda. All rights reser ved

families, community groups and so forth (Rainie and

Wellman, 2012). The social operating system, as

Rainie and Wellman (2012) mentioned, is a term

which describes the process of which individuals

interact and communicate and exchange information

one another. The existence of tools which can

facilitate people to manage their own social

networks has a profound impact on their social

operating system, because technologies such as the

Internet and mobile devices are a prerequisite for

networked individualism.

In networked individualism the focus lies on

person-to-person relationships instead of person-to-

group. A group as defined by Christakis and Fowler

(2009) is a collection of individuals within

population who share common attributes and

characteristicts, such as students in a particular class,

a religious group, a family and so forth. Meanwhile,

social network involves specific person-to-person

relationship within the group. This argumentation

can be interpreted that it is the content which

becomes the focus of the relationship, without taking

personal affiliation toward a group into account.

Networked individualism has some social

operating system features (Rainie and Wellman,

2012). These features involve:

a. Personal – The individual is totally autonomus

and powerful to their own social network.

Individual’s autonomy to socialize and to

customize lists of friends of whom he/she will

engange more tightly in a relationship can be

seen fromhow the individual categorize their

networks which serve as social supports or

another support without group limitations.

b. Multiuser – The individual are interacting with

people from various backgrounds. This indicates

that the individual can communicate with another

person diverse group and the individual’s

network will expand through connecting to the

network of the person he/she is interacting, the

network has never made a direct contact.

c. Multitasking – The individual performsa variety

of activities. Technology facilitates people to

arrange their daily activities so at one day,

people can carry out and adjust their activities.

d. Multithreaded – The individual caries out all or

some of their activities simultaneously.

Networked individuals involes people with

networked individualism characteristics. To get clear

on how individuals can be called as a networked

individual, some characteristics or aspects must be

met. The followings are the characteristics and

aspects of networked individualistic.

Hogan (2009) suggests two aspects of networked

individualism, namely variations in the network

structure and variations in interaction patterns.

Variations in the network structure indicate the form

of the network. Description of structure for each role

of each owned network can illustrate how tight and

close a group is. Thus, when ties between individual

is not really tight, the network is likely more

fragmented. Meanwhile, variations by interaction

patterns refer to strategies and channels which are

used to interact with each network.

1.2 Variations in Network Structure

Variations in network structure (VNS) show the

form of a particular network. Description of the role

structuresof each owned network reflects how dense

or close the group is, so the less dense network

presumably indicates a fragmented network (Hogan,

2009). A network with clear roles and structures can

be categorized as strong ties, while that with no

explicit role and structure is not classified as a

group, but a fragmented network (Hogan, 2009). In

the other words, a small group such as families and

colleagues has strong ties, while the isolated and

fragmented ties of the small group is called weak

ties, or weakest alters. Following a definition by

Rainie and Wellman (Rainie and Wellman, 2012) on

networked individualism, the focus of networked

individualism lies on the weak ties of network.

Network structure of networked individualism is

also focused on network selection. To a networked

individual, network is selectively found by the

individual, not because of merely affiliating in the

same group or living in the same environment.

Hence, it is also crucial to see how the network is

originally formed on individual basis, whether it is

given or personal choice. This can be seen also from

the aims of the SNS use. In the networking

dimension and an item of relieving stress dimension

of a study conducted by Kim, Shim, and Ahn (Kim,

Shim and Ahn, 2011), individual's motives to use

SNS include to maintain or to create new networks.

This assertion is consistent with the understanding of

the aspect of network selection, i.e., individuals

nowadays are not tied to a group or association due

to living in the same space or at the same time.

Instead, they selecttheir own network (Hogan,

2009).

1.3 Variations in Interaction Patterns

Variations in interaction patterns (VIP) refer to the

strategies and channels which are used to interact

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with their respective network (Hogan, 2009).

Variationsimply the existence of a new medium

which facilitates individuals to interact with their

respective network, allowing easier access for

person-to-person interaction than for place-to-place

interactions (Hogan, 2009).Variations in interaction

patterns are divided into two aspects, namely

multichannel and online interaction.

The multichannel sub aspect is related to the

number of communication channels used, such as

phone, chat, video call, email, and SMS.

Multichannel is classified as a sub-aspect of

interaction patternvariations in this study because it

adapts Park et al (2014), where they measured the

number of commucation channels as an indicator for

networked individualism measurement. This

measure is similar to Hogan's explanation onthe

interaction pattern variations.

Online interaction, meanwhile, measure to what

extent the individuals tend to interact with his/her

weak ties in the internet. This measure was adapted

from Park, et al (2014), where they employed

interaction with weak ties and an indicator for

networked individualism.

The phenomenon of networked

individualism can not be separated from the

development of information communication

technology (ICT). The development of ICT,

according to Rainie and Wellman (2012), gave birth

to three revolutions that became the platform for

network individualism, i.e., the social network

revolution, the internet revolution and the mobile

revolution. The rapid development of ICT made it

easier for people to expand their networks or social

relationship and have more freedom to socialize,

without any limitation in space and time.Moreover,

the development of ICT also gave more access to a

more effective communication and an ease to collect

various kind of information. People have the

convenience not just to use information, but also to

create and share their own content.Lastly, the

development of ICT, especially the development of

any kind of mobile gadget, gave people ability to

reach out and to be reach out by others easily. So,

because of the development of ICT, especially the

social medias, everyonecould make dan change

theirown network by ease.

Networked individualism put the individual user

as the centerhis/her own universe.That is why

network individualistic person more rely on his/her

personal network, not just on family or collegues

from school/work. Willard (2009) mention that

social media enable individuals to maintain and

develop connections with other people, and by

linking together all his/her networks on all social

medias, each individuals could learn about new

ideas and social movements as their friends and

collegues become involved in them.It means,

network individualistic person learns from the

network, especially via social media, more than from

his/her traditional groups.

Kemp (2017) showed that internet use in

Southeast Asia reached 339 million people, or more

than 50% of its population. Internet users in

Southeast Asia increased by 31% (+80 million) since

January 2016. In Indonesia alone, the increase was

51% (+45 million). If the number of Indonesian

population compared with the number of its internet

users, then the number of internet users in Indonesia

reached 51% (Kemp, 2017), or we can say that more

than half of the population of Indonesia is already

using the internet. In 2018, Kemp (2018) in his

report shows that internet users in Indonesia spent

more that 8 hours per day for using the internet via

any device. In case of social media, the growth of

social media users in Indonesia reach 23% per year

(Kemp, 2018). Considering the condition of internet

penetration and its development in Indonesia, there

is a suspicion that the phenomenon of network

individualism has also occurred in Indonesia. That

suspicion is raised as the main research problem for

present study: What is the description of the

networked individualistic tendency level of young

adults in Jabodetabek?

2 RESEARCH METHOD

This reseach is a descriptive study conducted using a

quantitative approach. The present study is non-

experimental because it did not manipulate varibles

but describes indicator of networked individualism

behaviour.

The level of the networked individualistic

tendency was measured by looking at variations in

network structure and interaction patterns. The

aspects of network structure variations were

measured by the weak ties sub aspect and network

selection, while those of interaction pattern

variations were measured by multichannel sub

aspect and online interaction. The measurement

which was used in this study involved a motivational

measurement tool adapted from Kim, Shim, and Ahn

(2011) and Park et al (2014). The measurement for

the SNS motives by Kim, Shim, and Ahn (2011)

consists of 13 items which covers four main motives

of the SNS usage: networking, collecting

information, relieving stress, and recording one's

Description of the Networked Individualistic Tendency Level of Young Adults in Jabodetabek

history. The primary motives of networking and

collecting information is categorized as external

motivation, while stress relieving and recording

one's history is classified as intrinsic motivation

(Kim, Shim and Ahn, 2011).

Measurement of network structure variations

Variations in the network structure are measured

based on the interaction between two sub-aspects,

namely the weak ties and the individual network

selection. Weak ties refer to the number of less

involved networks or relationships individuals have.

Internalmotivation is measured to evaluate

individuals’ motives to use the SNS. To measure

weak ties, this study adapted the measurement tool

by Park et al (2014). They measured weak ties by

evaluating the number of less involved networks

individuals have. To do this they calculate the

number of networks participants’ have, and then

reduce it with the number of less involved networks

they have. This study measures the number of

participants’ networks by asking participants to

calculate the number of their networks within their

SNS.

Measurement of network selection was adapted

from Kim, Shim, and Ahn (2011). The instrument

measures participants’ motives for the SNS use,

which is divided into external and intrinsic motives.

This studyfocused on networking dimensions and an

item of relieving stress dimension, which is about

finding a new network.After measuring these two

sub aspects, the two were combined to measure

variations in network structure. The mean from total

score of both weak ties and network selection was

calculated to subsequently classify participants into

three categories, including: low, moderate, and high.

Afterwards, the total score of the two sub-aspects

were multiplied to find out appropriate category for

respondents’ variation level, i.e., no variation, low

variation, moderate variation, and high variation.

Measurement of interaction pattern variations

Variations in interaction patterns were measured

using interaction between two aspects, which is

multichannel and online interactions. Multi channel,

as previously described, represent the number of

individual’s channel of communication with their

respective networks. While multichannel is about the

types of channels that are being used for

communication, online interaction defines the

intensity of an individual’s interaction with their

networks through an online channel. The

measurement that has been used in this study is by

adapting Park et al (2014) research regarding the

frequency of the participants usage of their various

channel of communications. There are six types of

communications used for the study; face-to-face,

phone call, email, video call, chatting, and text

messaging.

These two aspects were combined to calculate

variations of the interaction pattern. This was

conducted by calculatingmean of the scoresobtained

from both the multichannel and online interaction

questionnaire toclassify the participants into three

categories: low, medium, and high. Then, the total

score of each two sub-aspects were multiplied to

determine category of participants’ variation level,

namely: no variation, low variation, moderate

variation, and high variation.

Data analysis using crosstabulation were

performed to determine the tendency of individual

networks towards network structure and interaction

pattern variation. The cut-off scores for both aspects

of network structure and interaction pattern variation

are: no variation (.394 > X), moderate variation (.394

≤ X < 2.7), and high variation (X ≥ 2.7).

3 RESULT

Participants of this study involve community

residents of Jabodetabekwhich consist of a group of

19-27 years-old adults living in Jabodetabek. Most

of participants are university students, although

some reported as permanent employees.

Participants’ profile showed that most percentage of

participants in this study aged 22 years-old with 21

participants (40%).

Table 1: Networked individual tendency.

Frequency Percentage

Low 3 5.7%

Moderate 18 34%

High 32 60.4%

Total 53 100%

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Table 2: Description of the NIT according to VNS and VIP.

Level of networked individualistic tendency (NIT)

Total

Low Moderate Hi

VNS

No variation

(NV)

VIP

V0 0 0

LV 0 0 0

MV 2 0 0

HV 0 14 0

Low variation

(LV)

VIP

NV 0 0 0

LV 0 0 0

MV 0 0 0

HV 0 0 0

Moderate

variation (MV)

VIP

NV 1 0 0

LV 0 0 0

MV 0 4 0

HV 0 0 28

High variation

(HV)

VIP

NV 0 0 0

LV 0 0 0

MV 0 0 0

HV 0 0 4

Total 31832

The result of networked individual shows that

the participants of this study can be divided into two

groups, a group with moderate level of the

networked individual tendency (NIT) and another

group with the highlevel of tendency.

Based on the table 2, the interaction between

Variations in Interaction Patterns (VIP) and

Variations in Network Structure (VNS) shows that

most participants are in the moderate VNSwith 33

participants. Furthermore, the data shows that the

participants are more dominant in high NIT with a

total of 32 participants.

However, when analyzing the VIP, the data

indicatesthat 46 participants are classified in high

variation. Therefore, if participants have high VIP

and high or moderate VNS, they will have high NIT

because the table indicated that 4 participants have

high VIP and high VNS, while 28 participants have

high NIT although their VIP are high, their VNS are

moderate. Moderate NIT was indicated for 18

participants, and 14 participants have high VIP but

no variation of VNS. Furthermore, only 4

participants have moderate NIT with moderate VNS

and VIP. There are 3 participants who have the low

NIT, two of whom have moderate VIP and no

variation of VNS, while the other one participants

show no variation of VIP and moderate VNS.

4 DISCUSSION

From the result above, young adults living in

Jabodetabek have high networked individualistic

tendency, with emphasize on some aspects that need

to be seen including variations in network structure

and interaction pattern. When individuals’ variations

in interaction patterns are high, the study found that

the networked individual tendency is also high. This

illustration is similar to the variations in network

structure, i.e., when the network structure variation

is high, the networked individualistic tendency is

also high.

The result of interaction between interaction

pattern and network structure variations on the

networked individualistic tendency showed that the

level of variations in interaction patterns have a

significant effect on determining the level of

networked individualistic tendency. Individuals’

interaction patterns are an indicator to see networked

individualistic tendency because the individuals are

Description of the Networked Individualistic Tendency Level of Young Adults in Jabodetabek

able to communicate to interact with others,

independent of the group. Rainie dan Wellman

(2012) argued that an individual has power to

regulate how they will interact with another from

each network. Thus, the interaction between

interaction pattern variations and networked

individualistic tendency indicated that the

individuals’ ability to interact with their network can

be a valid measurement to evaluate individuals’

power because a networked individual is a person

who has power to their network without dependency

on their group.

These findingscan have significants impacts on

how to change people to learn about any issues.

Young adults in Jabodetabek learn more from their

online peers, than their traditional groups, either

family nor school/work’s collegues. They can have

topics that may not have been discussed or even not

opened to discuss on their traditional groups.

Meanwhile, networked individualism give

opportunity for everyone to have the same

knowledge, so high networked individualistic

tendencymeans that the opportunity for equality for

everyone in every area is something that can be

reached.

5 CONCLUSION

The variations in network structure based on

interaction between weak ties and network selection

showed that young adults in Jabodetabekhave high

weak ties.Individuals who have moderate network

selection have moderate network structure, while

those with low network selection showed no

variations in their network structure.

The variations in interaction patterns, based on

interaction between multichannel and online

interaction, showed that young adults in

Jabodetabekhave more specific interaction

strategies. They actively use more than a single

communication channel and they have high

interaction patterns. Both sub aspect of interaction

pattern variations, which is multichannel and online

interaction, showed that both aspectsare

predominantly high. Therefore, the aspect of

variations in interaction patterns needs high scores

for both sub aspects.

From the analysis, it can be concluded that most

of the young adults in Jabodetabek area have a high

networked individual tendency. And, the networked

individual’s level is determined by the level of

variations in interaction patterns.

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