research-article

Outage detection via real-time social stream analysis: leveraging the power of online complaints

Authors:

Eriq Augustine,

Cailin Cushing,

Kimberly Paterson,

Matt TognettiAuthors Info & Claims

WWW '12 Companion: Proceedings of the 21st International Conference on World Wide Web

Pages 13 - 22

https://doi.org/10.1145/2187980.2187983

Published: 16 April 2012 Publication History

Abstract

Over the past couple of years, Netflix has significantly expanded its online streaming offerings, which now encompass multiple delivery platforms and thousands of titles available for instant view. This paper documents the design and development of an outage detection system for the online services provided by Netflix. Unlike other internal quality-control measures used at Netflix, this system uses only publicly available information: the tweets, or Twitter posts, that mention the word "Netflix," and has been developed and deployed externally, on servers independent of the Netflix infrastructure. This paper discussed the system and provides assessment of the accuracy of its real-time detection and alert mechanisms.

References

[1]

A. Culotta. Detecting influenza outbreaks by analyzing twitter messages. InKDD Workshop on Social Media Analytics, 2010.

Digital Library

[2]

M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and I. H. Witten. The weka data mining software: an update.SIGKDD Explor. Newsl., 11(1):10--18, 2009.

Digital Library

[3]

L. Hong and B. D. Davison. Empirical study of topic modeling in twitter. In Proceedings of the First Workshop on Social Media Analytics, SOMA '10, pages 80--88, New York, NY, USA, 2010. ACM.

Digital Library

[4]

F. Jabr. Using twitter to follow trends beats the stock market.NewScientist, (2829), Sept. 2011. http://www.newscientist.com/article/mg21128295.900-using-twitter-to-follow-trends-beats-the-stock-market.html.

[5]

K. Levchenko, B. Meeder, M. Motoyama, S. Savage, and G. M. Voelker. Measuring online service availability using twitter. In Proc. of the 3rd Workshop on Online Social Networks (WOSN 2010), 2010.

Digital Library

[6]

B. Liu. Web Data Mining. Springer, 2007.

[7]

Y. Matsu, M. Okazak, and T. Sakak. Earthquake shakes twitter users: real-time event detection by social sensors. In WWW 2010: Proceedings of the 19th World Wide Web Conference, 2010. http://ymatsuo.com/papers/www2010.pdf.

Digital Library

[8]

Y. Matsuo and M. Ishizuka. Keyword extraction from a single document using word co-occurrence statistical information. In Proceedings of the 16th International FLAIRS Conference, pages 293--296, 2003.

[9]

NIST/SEMATECH. 6.4.3.1. single exponential smoothing. e-Handbook of Statistical Methods. http://www.itl.nist.gov/div898/handbook/.

[10]

NIST/SEMATECH. 6.4.3.2. double exponential smoothing. e-Handbook of Statistical Methods. http://www.itl.nist.gov/div898/handbook/.

[11]

B. O'Connor, R. Balasubramanyan, B. R. Routledge, and N. A. Smith. From tweets to polls: Linking text sentiment to public opinion time series. In Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media, pages 122--129. AAAI Press, 2010.

[12]

M. F. Porter. An algorithm for suffix stripping. In K. Sparck Jones and P. Willett, editors,Readings in information retrieval, pages 313--316. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 1997. http://tartarus.org/martin/PorterStemmer.

Digital Library

[13]

E. R. Tufte. Visual Explanations: Images and Quantities, Evidence and Narrative. Graphics Press, first edition edition, February 1997.

Digital Library

[14]

Twitter. #numbers, Mar. 2011. http://blog.twitter.com/2011/03/numbers.html.

[15]

K. Weil. NoSQL at twitter, 2010. Presented at Strange Loop conference.

Cited By

Arazzi MMurer DNicolazzo SNocera A(2023)How COVID-19 affects user interaction with online streaming service providers on twitterSocial Network Analysis and Mining10.1007/s13278-023-01143-313:1Online publication date: 16-Oct-2023
https://doi.org/10.1007/s13278-023-01143-3
Kergl DRoedler RRodosek G(2017)Towards Internet Scale Quality-of-Experience Measurement with TwitterSecurity of Networks and Services in an All-Connected World10.1007/978-3-319-60774-0_8(108-122)Online publication date: 17-Jun-2017
https://doi.org/10.1007/978-3-319-60774-0_8
Kergl D(2015)Enhancing Network Security by Software Vulnerability Detection Using Social Media Analysis Extended AbstractProceedings of the 2015 IEEE International Conference on Data Mining Workshop (ICDMW)10.1109/ICDMW.2015.228(1532-1533)Online publication date: 14-Nov-2015
https://dl.acm.org/doi/10.1109/ICDMW.2015.228
Show More Cited By

Index Terms

Outage detection via real-time social stream analysis: leveraging the power of online complaints
1. Applied computing
  1. Law, social and behavioral sciences
    1. Sociology
2. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Language resources

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Published In

cover image ACM Other conferences

WWW '12 Companion: Proceedings of the 21st International Conference on World Wide Web

April 2012

1250 pages

ISBN:9781450312301

DOI:10.1145/2187980

General Chairs:
Alain Mille
Université de Lyon, France
,
Fabien Gandon
INRIA, France
,
Jacques Misselis
HP, France
,
Program Chairs:
Michael Rabinovich
Case Western Reserve University, USA
,
Steffen Staab
University of Koblenz-Landau, Germany

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Univ. de Lyon: Universite de Lyon

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 April 2012

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WWW 2012

Sponsor:

Univ. de Lyon

WWW 2012: 21st World Wide Web Conference 2012

April 16 - 20, 2012

Lyon, France

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

Arazzi MMurer DNicolazzo SNocera A(2023)How COVID-19 affects user interaction with online streaming service providers on twitterSocial Network Analysis and Mining10.1007/s13278-023-01143-313:1Online publication date: 16-Oct-2023
https://doi.org/10.1007/s13278-023-01143-3
Kergl DRoedler RRodosek G(2017)Towards Internet Scale Quality-of-Experience Measurement with TwitterSecurity of Networks and Services in an All-Connected World10.1007/978-3-319-60774-0_8(108-122)Online publication date: 17-Jun-2017
https://doi.org/10.1007/978-3-319-60774-0_8
Kergl D(2015)Enhancing Network Security by Software Vulnerability Detection Using Social Media Analysis Extended AbstractProceedings of the 2015 IEEE International Conference on Data Mining Workshop (ICDMW)10.1109/ICDMW.2015.228(1532-1533)Online publication date: 14-Nov-2015
https://dl.acm.org/doi/10.1109/ICDMW.2015.228
Kergl DRoedler RRodosek G(2015)Detection of Zero Day Exploits Using Real-Time Social Media StreamsAdvances in Nature and Biologically Inspired Computing10.1007/978-3-319-27400-3_36(405-416)Online publication date: 18-Nov-2015
https://doi.org/10.1007/978-3-319-27400-3_36
Djatmiko MSchatzmann DDimitropoulos XFriedman ABoreli RAlmeroth KMathy LPapagiannaki KMisra V(2013)Federated flow-based approach for privacy preserving connectivity trackingProceedings of the ninth ACM conference on Emerging networking experiments and technologies10.1145/2535372.2535388(429-440)Online publication date: 9-Dec-2013
https://dl.acm.org/doi/10.1145/2535372.2535388
Lipford HZurko MFord RZurko MHerley CWhalen T(2012)Someone to watch over meProceedings of the 2012 New Security Paradigms Workshop10.1145/2413296.2413303(67-76)Online publication date: 18-Sep-2012
https://dl.acm.org/doi/10.1145/2413296.2413303

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