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https://doi.org/10.1109/comsne...
Article . 2016 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2015
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
DBLP
Article . 2015
Data sources: DBLP
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Shifting behaviour of users: Towards understanding the fundamental law of Social Networks

Authors: Yayati Gupta; Jaspal Singh Saini; Nidhi Sridhar; S. R. S. Iyengar;

Shifting behaviour of users: Towards understanding the fundamental law of Social Networks

Abstract

Social Networking Sites (SNSs) are powerful marketing and communication tools. There are hundreds of SNSs that have entered and exited the market over time. The coexistence of multiple SNSs is a rarely observed phenomenon. Most coexisting SNSs either serve different purposes for its users or have cultural differences among them. The introduction of a new SNS with a better set of features can lead to the demise of an existing SNS, as observed in the transition from Orkut to Facebook. The paper proposes a model for analyzing the transition of users from one SNS to another, when a new SNS is introduced in the system. The game theoretic model proposed considers two major factors in determining the success of a new SNS. The first being time that an old SNS gets to stabilise. We study whether the time that a SNS like Facebook received to monopolize its reach had a distinguishable effect. The second factor is the set of features showcased by the new SNS. The results of the model are also experimentally verified with data collected by means of a survey.

Keywords

Social and Information Networks (cs.SI), FOS: Computer and information sciences, Physics - Physics and Society, FOS: Physical sciences, Computer Science - Social and Information Networks, Physics and Society (physics.soc-ph)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green