Structural analysis of the emerging event-web

Vivek K. Singh; Ramesh Jain

doi:10.1145/1772690.1772865

Structural analysis of the emerging event-web

Vivek K. Singh, Ramesh Jain

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

9 Scopus citations

Abstract

Events are the fundamental abstractions to study the dynamic world. We believe that the next generation of web (i.e. event-web), will focus on interconnections between events as they occur across space and time [3]. In fact we argue that the real value of large volumes of microblog data being created daily lies in its inherent spatio-temporality, and its correlation with the real-world events. In this context, we studied the structural properties of a corpus of 5,835,237 Twitter microblogs, and found it to exhibit Power laws across space and time, much like those exhibited by events in multiple domains. The properties studied over microblogs on different topics can be applied to study relationships between related events, as well as data organization for event-based, real-time, and location-aware applications.

Original language	American English
Title of host publication	Proceedings of the 19th International Conference on World Wide Web, WWW '10
Pages	1183-1184
Number of pages	2
DOIs	https://doi.org/10.1145/1772690.1772865
State	Published - 2010
Externally published	Yes
Event	19th International World Wide Web Conference, WWW2010 - Raleigh, NC, United States Duration: Apr 26 2010 → Apr 30 2010

Publication series

Name	Proceedings of the 19th International Conference on World Wide Web, WWW '10

Other

Other	19th International World Wide Web Conference, WWW2010
Country/Territory	United States
City	Raleigh, NC
Period	4/26/10 → 4/30/10

ASJC Scopus subject areas

Computer Networks and Communications
Computer Science Applications

Keywords

event-web
microblogs
pareto law
power law
zipfs law

Access to Document

10.1145/1772690.1772865

Cite this

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title = "Structural analysis of the emerging event-web",

abstract = "Events are the fundamental abstractions to study the dynamic world. We believe that the next generation of web (i.e. event-web), will focus on interconnections between events as they occur across space and time [3]. In fact we argue that the real value of large volumes of microblog data being created daily lies in its inherent spatio-temporality, and its correlation with the real-world events. In this context, we studied the structural properties of a corpus of 5,835,237 Twitter microblogs, and found it to exhibit Power laws across space and time, much like those exhibited by events in multiple domains. The properties studied over microblogs on different topics can be applied to study relationships between related events, as well as data organization for event-based, real-time, and location-aware applications.",

keywords = "event-web, microblogs, pareto law, power law, zipfs law",

author = "Singh, {Vivek K.} and Ramesh Jain",

year = "2010",

doi = "10.1145/1772690.1772865",

language = "American English",

isbn = "9781605587998",

series = "Proceedings of the 19th International Conference on World Wide Web, WWW '10",

pages = "1183--1184",

booktitle = "Proceedings of the 19th International Conference on World Wide Web, WWW '10",

note = "19th International World Wide Web Conference, WWW2010 ; Conference date: 26-04-2010 Through 30-04-2010",

}

Singh, VK & Jain, R 2010, Structural analysis of the emerging event-web. in Proceedings of the 19th International Conference on World Wide Web, WWW '10. Proceedings of the 19th International Conference on World Wide Web, WWW '10, pp. 1183-1184, 19th International World Wide Web Conference, WWW2010, Raleigh, NC, United States, 4/26/10. https://doi.org/10.1145/1772690.1772865

TY - GEN

T1 - Structural analysis of the emerging event-web

AU - Singh, Vivek K.

AU - Jain, Ramesh

PY - 2010

Y1 - 2010

N2 - Events are the fundamental abstractions to study the dynamic world. We believe that the next generation of web (i.e. event-web), will focus on interconnections between events as they occur across space and time [3]. In fact we argue that the real value of large volumes of microblog data being created daily lies in its inherent spatio-temporality, and its correlation with the real-world events. In this context, we studied the structural properties of a corpus of 5,835,237 Twitter microblogs, and found it to exhibit Power laws across space and time, much like those exhibited by events in multiple domains. The properties studied over microblogs on different topics can be applied to study relationships between related events, as well as data organization for event-based, real-time, and location-aware applications.

AB - Events are the fundamental abstractions to study the dynamic world. We believe that the next generation of web (i.e. event-web), will focus on interconnections between events as they occur across space and time [3]. In fact we argue that the real value of large volumes of microblog data being created daily lies in its inherent spatio-temporality, and its correlation with the real-world events. In this context, we studied the structural properties of a corpus of 5,835,237 Twitter microblogs, and found it to exhibit Power laws across space and time, much like those exhibited by events in multiple domains. The properties studied over microblogs on different topics can be applied to study relationships between related events, as well as data organization for event-based, real-time, and location-aware applications.

KW - event-web

KW - microblogs

KW - pareto law

KW - power law

KW - zipfs law

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U2 - 10.1145/1772690.1772865

DO - 10.1145/1772690.1772865

M3 - Conference contribution

SN - 9781605587998

T3 - Proceedings of the 19th International Conference on World Wide Web, WWW '10

SP - 1183

EP - 1184

BT - Proceedings of the 19th International Conference on World Wide Web, WWW '10

T2 - 19th International World Wide Web Conference, WWW2010

Y2 - 26 April 2010 through 30 April 2010

ER -

Structural analysis of the emerging event-web

Abstract

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Other

ASJC Scopus subject areas

Keywords

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