A tree-network model for mining short message services seed users and its empirical analysis

Yongli Li; Chong Wu; Xudong Wang; Shitang Wu

doi:10.1016/j.knosys.2012.11.010

A tree-network model for mining short message services seed users and its empirical analysis

Yongli Li
, Chong Wu^*
, Xudong Wang
, Shitang Wu

^*Corresponding author for this work

School of Management, Harbin Institute of Technology
Beijing Institute of Information and Control

Research output: Contribution to journal › Article › peer-review

9 Scopus citations

Abstract

Identifying short message services (SMSs) seed users helps to discover the information's originals and transmission paths. A tree-network model was proposed to depict the characteristics of SMS seed users who have such three features as "ahead of time", "mass texting" and "numerous retransmissions". For acquiring the established network model's width and depth, a clustering algorithm based on density was adopted and a recursion algorithm was designed to solve such problems. An objective, comprehensive and scale-free evaluation function was further presented to rank the potential seed users by using the width and the depth obtained above. Furthermore, the model's empirical analysis was made based on part of the Shenzhen's cell phone SMS data in February of 2012. The model is effective and applicable as a powerful tool to solve the SMS seed users' mining problem.

Original language	English
Pages (from-to)	50-57
Number of pages	8
Journal	Knowledge-Based Systems
Volume	40
DOIs	https://doi.org/10.1016/j.knosys.2012.11.010
State	Published - Mar 2013
Externally published	Yes

Keywords

Data mining
Evaluation
Information management
Network analysis
Seed users

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10.1016/j.knosys.2012.11.010

Cite this

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title = "A tree-network model for mining short message services seed users and its empirical analysis",

abstract = "Identifying short message services (SMSs) seed users helps to discover the information's originals and transmission paths. A tree-network model was proposed to depict the characteristics of SMS seed users who have such three features as {"}ahead of time{"}, {"}mass texting{"} and {"}numerous retransmissions{"}. For acquiring the established network model's width and depth, a clustering algorithm based on density was adopted and a recursion algorithm was designed to solve such problems. An objective, comprehensive and scale-free evaluation function was further presented to rank the potential seed users by using the width and the depth obtained above. Furthermore, the model's empirical analysis was made based on part of the Shenzhen's cell phone SMS data in February of 2012. The model is effective and applicable as a powerful tool to solve the SMS seed users' mining problem.",

keywords = "Data mining, Evaluation, Information management, Network analysis, Seed users",

author = "Yongli Li and Chong Wu and Xudong Wang and Shitang Wu",

year = "2013",

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doi = "10.1016/j.knosys.2012.11.010",

language = "英语",

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pages = "50--57",

journal = "Knowledge-Based Systems",

issn = "0950-7051",

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T1 - A tree-network model for mining short message services seed users and its empirical analysis

AU - Li, Yongli

AU - Wu, Chong

AU - Wang, Xudong

AU - Wu, Shitang

PY - 2013/3

Y1 - 2013/3

N2 - Identifying short message services (SMSs) seed users helps to discover the information's originals and transmission paths. A tree-network model was proposed to depict the characteristics of SMS seed users who have such three features as "ahead of time", "mass texting" and "numerous retransmissions". For acquiring the established network model's width and depth, a clustering algorithm based on density was adopted and a recursion algorithm was designed to solve such problems. An objective, comprehensive and scale-free evaluation function was further presented to rank the potential seed users by using the width and the depth obtained above. Furthermore, the model's empirical analysis was made based on part of the Shenzhen's cell phone SMS data in February of 2012. The model is effective and applicable as a powerful tool to solve the SMS seed users' mining problem.

AB - Identifying short message services (SMSs) seed users helps to discover the information's originals and transmission paths. A tree-network model was proposed to depict the characteristics of SMS seed users who have such three features as "ahead of time", "mass texting" and "numerous retransmissions". For acquiring the established network model's width and depth, a clustering algorithm based on density was adopted and a recursion algorithm was designed to solve such problems. An objective, comprehensive and scale-free evaluation function was further presented to rank the potential seed users by using the width and the depth obtained above. Furthermore, the model's empirical analysis was made based on part of the Shenzhen's cell phone SMS data in February of 2012. The model is effective and applicable as a powerful tool to solve the SMS seed users' mining problem.

KW - Data mining

KW - Evaluation

KW - Information management

KW - Network analysis

KW - Seed users

UR - https://www.scopus.com/pages/publications/84872976250

U2 - 10.1016/j.knosys.2012.11.010

DO - 10.1016/j.knosys.2012.11.010

M3 - 文章

AN - SCOPUS:84872976250

SN - 0950-7051

VL - 40

SP - 50

EP - 57

JO - Knowledge-Based Systems

JF - Knowledge-Based Systems

ER -

A tree-network model for mining short message services seed users and its empirical analysis

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Keywords

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