paper published on the 6th ICOICT 2018 http://www.icoict.org

1. Andry Alamsyah, Made Kevin Bratawisnu, Puput Hari Sanjani
Lab. Social Computing and Big Data
School of Economics and Business, Telkom University, Bandung, Indonesia
Finding Pattern in Dynamic Network Analysis

2. Introduction
People increasingly look at social media applications as an
important part of their daily life and more likely to move their
interactions to the virtual platforms.

3. Exploring Pattern of User Interaction
NETWORK PROPERTIES EXPLANATION
Network Properties Explanation
Nodes Represent the positions held by users within the network [13]
Edges Reflects the relationship between users or entities that occur in
the network [13]
Average Degree Determined by the number of relationships on one node
divided by the number of relationships that occur on one social
network [7]
Diameter The furthest distance between any pair of nodes [14]
Average Path Length The average path length between any pair of nodes [14]

4. Research Design and Methodology
Data Collection Data Preprocessing
Network Properties
Measurement
Result and
Conclusion DNA Construction
SNA Model
Construction

5. Research Design and Methodology
TABLE II. RESULT OF CRAWLING DATA ON TWITTER
Keywords (e-commerce) Amount of Data
Lazada 105.222 tweets
Tokopedia 38.405 tweets
Elevenia 22.162 tweets
Keywords (telecommunication) Amount of Data
Telkomsel 94.128 tweets
Indosat 30.042 tweets

6. Result and Analysis
Lazada Tokopedia Elevenia

7. Result and Analysis
Telkomsel Indosat

8. Result and Analysis
COMPARISON OF SOCIAL NETWORK PROPERTIES
A. Network Properties of E-commerce Business
Network Properties Lazada Tokopedia Elevenia
Nodes 47.398 9.897 3.755
Edges 50.385 10.301 5.358
Average Degree 2,13 2,08 2,04
Diameter 24 14 10
Average Path Length 7,25 4,08 3,88
B. Network Properties of Telecomunication Industry
Network Properties Telkomsel Indosat
Nodes 14.878 16.599
Edges 14.972 17.868
Diameter 24 17
Average Degree 2,013 2,153
Average Path Length 3,518 3,721

9. Result and Analysis
This shows the number of actors who joined or leaved in social networks during the study period. Actors
interact on social networks dominated during the workdays than weekend.
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Lazada Tokopedia Elevenia

10. Result and Analysis
This explain an analysis of amount the information circulated in social networks during the study period.
Information or interactions that possibly tweets, retweets, mention and reply on social media Twitter most
on workdays in every week.
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Lazada Tokopedia Elevenia

11. Result and Analysis
This pattern of movement possibly used by the company for information that the average of relationships
that occur have a high value so that the dissemination of information will spread widely that is on workdays
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Average Degree
Lazada Tokopedia Elevenia

12. Result and Analysis
The useful information in that figure for a business is about when the largest distance in the network has the
lowest value so that the distance of the furthest actor is small resulting in faster information circulating. The
lowest diameter often occurs during weekend.
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Diameter
Lazada Tokopedia Elevenia

13. Result and Analysis
That figure provides information to understand when there is a change in the network structure that reduces
the average amount of distance between two users on the network. It may help seen that the average path
length value formed has the smallest value during weekend..
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Average Path Length
Lazada Tokopedia Elevenia

14. Conclusion
We conclude that the organization have the ability to take advantage of
promotional time during workdays (Monday-Friday). We describe as when
many actors and interactions happen at that time. However, the
organization have the possibility to disseminate information during
weekend (Saturday-Sunday) when the diameter and average path length
remain low. The lowest value of diameter and average path length will
speed up the information dissemination.