FAST

Forecast and analytics of social media and traffic

Venkata Rama Kiran Garimella, Carlos Castillo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

We present FAST (http://fast.qcri.org/), a platform for real-time trafic predictions in online news sources. FAST accurately forecasts the future number of page views of an article based on user trafic and social media engagement signals. To our knowledge, this is the first industrial scale, real-time system for predictive web analytics.

Original languageEnglish
Title of host publicationProceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW
PublisherAssociation for Computing Machinery
Pages13-16
Number of pages4
ISBN (Print)9781450325417
DOIs
Publication statusPublished - 1 Jan 2014
Event17th ACM Conference on Computer Supported Cooperative Work and Social Computing, CSCW 2014 - Baltimore, MD, United States
Duration: 15 Feb 201419 Feb 2014

Other

Other17th ACM Conference on Computer Supported Cooperative Work and Social Computing, CSCW 2014
CountryUnited States
CityBaltimore, MD
Period15/2/1419/2/14

Fingerprint

Real time systems

Keywords

  • News media
  • Social media
  • Web analytics

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Human-Computer Interaction

Cite this

Garimella, V. R. K., & Castillo, C. (2014). FAST: Forecast and analytics of social media and traffic. In Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW (pp. 13-16). Association for Computing Machinery. https://doi.org/10.1145/2556420.2556784

FAST : Forecast and analytics of social media and traffic. / Garimella, Venkata Rama Kiran; Castillo, Carlos.

Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW. Association for Computing Machinery, 2014. p. 13-16.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Garimella, VRK & Castillo, C 2014, FAST: Forecast and analytics of social media and traffic. in Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW. Association for Computing Machinery, pp. 13-16, 17th ACM Conference on Computer Supported Cooperative Work and Social Computing, CSCW 2014, Baltimore, MD, United States, 15/2/14. https://doi.org/10.1145/2556420.2556784
Garimella VRK, Castillo C. FAST: Forecast and analytics of social media and traffic. In Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW. Association for Computing Machinery. 2014. p. 13-16 https://doi.org/10.1145/2556420.2556784
Garimella, Venkata Rama Kiran ; Castillo, Carlos. / FAST : Forecast and analytics of social media and traffic. Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW. Association for Computing Machinery, 2014. pp. 13-16
@inproceedings{974f3a74f5fe41fb8543e5d02559e609,
title = "FAST: Forecast and analytics of social media and traffic",
abstract = "We present FAST (http://fast.qcri.org/), a platform for real-time trafic predictions in online news sources. FAST accurately forecasts the future number of page views of an article based on user trafic and social media engagement signals. To our knowledge, this is the first industrial scale, real-time system for predictive web analytics.",
keywords = "News media, Social media, Web analytics",
author = "Garimella, {Venkata Rama Kiran} and Carlos Castillo",
year = "2014",
month = "1",
day = "1",
doi = "10.1145/2556420.2556784",
language = "English",
isbn = "9781450325417",
pages = "13--16",
booktitle = "Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW",
publisher = "Association for Computing Machinery",

}

TY - GEN

T1 - FAST

T2 - Forecast and analytics of social media and traffic

AU - Garimella, Venkata Rama Kiran

AU - Castillo, Carlos

PY - 2014/1/1

Y1 - 2014/1/1

N2 - We present FAST (http://fast.qcri.org/), a platform for real-time trafic predictions in online news sources. FAST accurately forecasts the future number of page views of an article based on user trafic and social media engagement signals. To our knowledge, this is the first industrial scale, real-time system for predictive web analytics.

AB - We present FAST (http://fast.qcri.org/), a platform for real-time trafic predictions in online news sources. FAST accurately forecasts the future number of page views of an article based on user trafic and social media engagement signals. To our knowledge, this is the first industrial scale, real-time system for predictive web analytics.

KW - News media

KW - Social media

KW - Web analytics

UR - http://www.scopus.com/inward/record.url?scp=84899002946&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84899002946&partnerID=8YFLogxK

U2 - 10.1145/2556420.2556784

DO - 10.1145/2556420.2556784

M3 - Conference contribution

SN - 9781450325417

SP - 13

EP - 16

BT - Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW

PB - Association for Computing Machinery

ER -