Determining an author's native language by mining a text for errors

Moshe Koppel; Jonathan Schler; Kfir Zigdon

doi:10.1145/1081870.1081947

Determining an author's native language by mining a text for errors

Moshe Koppel, Jonathan Schler, Kfir Zigdon

Department of Computer Science

Bar-Ilan University

Research output: Contribution to conference › Paper › peer-review

134 Scopus citations

Abstract

In this paper, we show that stylistic text features can be exploited to determine an anonymous author's native language with high accuracy. Specifically, we first use automatic tools to ascertain frequencies of various stylistic idiosyncrasies in a text. These frequencies then serve as features for support vector machines that learn to classify texts according to author native language.

Original language	English
Pages	624-628
Number of pages	5
DOIs	https://doi.org/10.1145/1081870.1081947
State	Published - 2005
Event	KDD-2005: 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - Chicago, IL, United States Duration: 21 Aug 2005 → 24 Aug 2005

Conference

Conference	KDD-2005: 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Country/Territory	United States
City	Chicago, IL
Period	21/08/05 → 24/08/05

Keywords

Author profiling
Text mining

Access to Document

10.1145/1081870.1081947

Cite this

@conference{58d922f004dd4661b7c87b323c6bf57b,

title = "Determining an author's native language by mining a text for errors",

abstract = "In this paper, we show that stylistic text features can be exploited to determine an anonymous author's native language with high accuracy. Specifically, we first use automatic tools to ascertain frequencies of various stylistic idiosyncrasies in a text. These frequencies then serve as features for support vector machines that learn to classify texts according to author native language.",

keywords = "Author profiling, Text mining",

author = "Moshe Koppel and Jonathan Schler and Kfir Zigdon",

year = "2005",

doi = "10.1145/1081870.1081947",

language = "אנגלית",

pages = "624--628",

note = "KDD-2005: 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining ; Conference date: 21-08-2005 Through 24-08-2005",

}

TY - CONF

T1 - Determining an author's native language by mining a text for errors

AU - Koppel, Moshe

AU - Schler, Jonathan

AU - Zigdon, Kfir

PY - 2005

Y1 - 2005

N2 - In this paper, we show that stylistic text features can be exploited to determine an anonymous author's native language with high accuracy. Specifically, we first use automatic tools to ascertain frequencies of various stylistic idiosyncrasies in a text. These frequencies then serve as features for support vector machines that learn to classify texts according to author native language.

AB - In this paper, we show that stylistic text features can be exploited to determine an anonymous author's native language with high accuracy. Specifically, we first use automatic tools to ascertain frequencies of various stylistic idiosyncrasies in a text. These frequencies then serve as features for support vector machines that learn to classify texts according to author native language.

KW - Author profiling

KW - Text mining

UR - http://www.scopus.com/inward/record.url?scp=32344439684&partnerID=8YFLogxK

U2 - 10.1145/1081870.1081947

DO - 10.1145/1081870.1081947

M3 - ???researchoutput.researchoutputtypes.contributiontoconference.paper???

AN - SCOPUS:32344439684

SP - 624

EP - 628

T2 - KDD-2005: 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Y2 - 21 August 2005 through 24 August 2005

ER -

Determining an author's native language by mining a text for errors

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this