Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Enabling Medical Translation for Low-Resource Languages Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Large Scale Authorship Attribution of Online Reviews

Authors : Prasha Shrestha, Arjun Mukherjee, Thamar Solorio

Published in: Computational Linguistics and Intelligent Text Processing

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Traditional authorship attribution methods focus on the scenario of a limited number of authors writing long pieces of text. These methods are engineered to work on a small number of authors and generally do not scale well to a corpus of online reviews where the candidate set of authors is large. However, attribution of online reviews is important as they are replete with deception and spam. We evaluate a new large scale approach for predicting authorship via the task of verification on online reviews. Our evaluation considers a large number of possible candidate authors seen to date. Our results show that multiple verification models can be successfully combined to associate reviews with their correct author in more than 78% of the time. We propose that our approach can be used to slow down or deter the number of deceptive reviews in the wild.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Aspect Terms Extraction of Arabic Dialects for Opinion Mining Using Conditional Random Fields
next chapter Discovering Correspondence of Sentiment Words and Aspects
Footnotes
1
The datasets can be obtained at http://​ritual.​uh.​edu/​resources/​.
 
Literature
1.
2.
3.
Kešelj, V., Peng, F., Cercone, N., Thomas, C.: N-gram-based author profiles for authorship attribution. In: Proceedings of the Conference of Pacific Association for Computational Linguistics, PACLING, vol. 3, pp. 255–264 (2003)
4.
Koppel, M., Schler, J.: Authorship verification as a one-class classification problem. In: Proceedings of the Twenty-First International Conference on Machine Learning, ICML 2004, p. 62. ACM, New York (2004)
5.
Koppel, M., Winter, Y.: Determining if two documents are written by the same author. J. Assoc. Inf. Sci. Technol. 65, 178–187 (2014)CrossRef
6.
Qian, T.Y., Liu, B., Li, Q., Si, J.: Review authorship attribution in a similarity space. J. Comput. Sci. Technol. 30, 200–213 (2015)CrossRef
7.
Stamatatos, E.: A survey of modern authorship attribution methods. J. Am. Soc. Inf. Sci. Technol. 60, 538–556 (2009)CrossRef
8.
9.
Jindal, N., Liu, B.: Opinion spam and analysis. In: Proceedings of the 2008 International Conference on Web Search and Data Mining, WSDM 2008, pp. 219–230. ACM, New York (2008)
10.
Mukherjee, A., Liu, B., Glance, N.: Spotting fake reviewer groups in consumer reviews. In: Proceedings of the 21st International Conference on World Wide Web, WWW 2012, pp. 191–200. ACM, New York (2012)
11.
Narayanan, A., Paskov, H., Gong, N., Bethencourt, J., Stefanov, E., Shin, E., Song, D.: On the feasibility of internet-scale author identification. In: 2012 IEEE Symposium on Security and Privacy (SP), pp. 300–314 (2012)
12.
Seroussi, Y., Zukerman, I., Bohnert, F.: Authorship attribution with topic models. Comput. Linguist. 40, 269–310 (2014)CrossRef
13.
Burrows, J.: Delta: a measure of stylistic difference and a guide to likely authorship. Literary Linguist. Comput. 17, 267–287 (2002)CrossRef
14.
Eder, M.: Does size matter? authorship attribution, small samples, big problem. Digit. Scholarsh. Humanit. 30, 167–182 (2015)CrossRef
15.
Stein, B., Lipka, N., Prettenhofer, P.: Intrinsic plagiarism analysis. Lang. Resour. Eval. 45, 63–82 (2011)CrossRef
16.
Guthrie, D., Guthrie, L., Allison, B., Wilks, Y.: Unsupervised anomaly detection. In: Proceedings of the 20th International Joint Conference on Artifical Intelligence, IJCAI 2007, San Francisco, CA, USA, pp. 1624–1628. Morgan Kaufmann Publishers Inc. (2007)
17.
Flesch, R.: A new readability yardstick. J. Appl. Psychol. 32, 221–223 (1948)CrossRef
18.
Kincaid, J.P., Fishburne Jr., R.P., Rogers, R.L., Chissom, B.S.: Derivation of new readability formulas (automated readability index, fog count and flesch reading ease formula) for navy enlisted personnel. Technical report (1975)
19.
Gunning, R.: The Technique of Clear Writing (1952)
20.
Metadata
Title
Large Scale Authorship Attribution of Online Reviews
Authors
Prasha Shrestha
Arjun Mukherjee
Thamar Solorio
Copyright Year
2018
Book
Computational Linguistics and Intelligent Text Processing

Print ISBN: 978-3-319-75486-4

Electronic ISBN: 978-3-319-75487-1

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-75487-1_17

Premium Partner

    Image Credits