Automating News Content Analysis: An Application to Gender Bias and Readability

Omar Ali; Ilias Flaounas; Tijl De Bie; Nick Mosdell; Justin Lewis; Nello Cristianini

Automating News Content Analysis: An Application to Gender Bias and Readability

Omar Ali, Ilias Flaounas, Tijl De Bie, Nick Mosdell, Justin Lewis, Nello Cristianini

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

Abstract

In this article we present an application of text-analysis technologies to support social science research, in particular the analysis of patterns in news content. We describe a system that gathers and annotates large volumes of textual data in order to extract patterns and trends. We have examined 3.5 million news articles and show that their topic is related to the gender bias and readability of their content. This study is intended to illustrate how pattern analysis technology can be deployed to automate tasks commonly performed by humans in the social sciences, in order to enable large scale studies that would otherwise be impossible.

Translated title of the contribution	Automating News Content Analysis: An Application to Gender Bias and Readability
Original language	English
Title of host publication	Proceedings of the First Workshop on Applications of Pattern Analysis (WAPA 2010)
Subtitle of host publication	1-3 September 2010, Cumberland Lodge, Windsor, UK
Publisher	Massachusetts Institute of Technology (MIT) Press
Pages	36-43
Number of pages	8
Publication status	Published - Sept 2010

Publication series

Name	JMLR Workshop and Conference Proceedings
Publisher	JMLR
Volume	11
ISSN (Print)	1938-7228

Bibliographical note

ISBN: 19387228
Publisher: JMLR: Workshop and Conference Proceedings
Name and Venue of Conference: Workshop on Applications of Pattern Analysis (WAPA)
Other identifier: 2001261

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Ali, O., Flaounas, I., Bie, T. D., Mosdell, N., Lewis, J., & Cristianini, N. (2010). Automating News Content Analysis: An Application to Gender Bias and Readability. In Proceedings of the First Workshop on Applications of Pattern Analysis (WAPA 2010): 1-3 September 2010, Cumberland Lodge, Windsor, UK (pp. 36-43). (JMLR Workshop and Conference Proceedings; Vol. 11). Massachusetts Institute of Technology (MIT) Press. http://proceedings.mlr.press/v11/ali10a.html

Ali, Omar ; Flaounas, Ilias ; Bie, Tijl De et al. / Automating News Content Analysis: An Application to Gender Bias and Readability. Proceedings of the First Workshop on Applications of Pattern Analysis (WAPA 2010): 1-3 September 2010, Cumberland Lodge, Windsor, UK. Massachusetts Institute of Technology (MIT) Press, 2010. pp. 36-43 (JMLR Workshop and Conference Proceedings).

@inproceedings{e34990c7c18a4732870fe10954a2a39f,

title = "Automating News Content Analysis: An Application to Gender Bias and Readability",

abstract = "In this article we present an application of text-analysis technologies to support social science research, in particular the analysis of patterns in news content. We describe a system that gathers and annotates large volumes of textual data in order to extract patterns and trends. We have examined 3.5 million news articles and show that their topic is related to the gender bias and readability of their content. This study is intended to illustrate how pattern analysis technology can be deployed to automate tasks commonly performed by humans in the social sciences, in order to enable large scale studies that would otherwise be impossible. ",

author = "Omar Ali and Ilias Flaounas and Bie, {Tijl De} and Nick Mosdell and Justin Lewis and Nello Cristianini",

note = "ISBN: 19387228 Publisher: JMLR: Workshop and Conference Proceedings Name and Venue of Conference: Workshop on Applications of Pattern Analysis (WAPA) Other identifier: 2001261",

year = "2010",

month = sep,

language = "English",

series = "JMLR Workshop and Conference Proceedings",

publisher = "Massachusetts Institute of Technology (MIT) Press",

pages = "36--43",

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}

Ali, O, Flaounas, I, Bie, TD, Mosdell, N, Lewis, J & Cristianini, N 2010, Automating News Content Analysis: An Application to Gender Bias and Readability. in Proceedings of the First Workshop on Applications of Pattern Analysis (WAPA 2010): 1-3 September 2010, Cumberland Lodge, Windsor, UK. JMLR Workshop and Conference Proceedings, vol. 11, Massachusetts Institute of Technology (MIT) Press, pp. 36-43. <http://proceedings.mlr.press/v11/ali10a.html>

Automating News Content Analysis: An Application to Gender Bias and Readability. / Ali, Omar; Flaounas, Ilias; Bie, Tijl De et al.
Proceedings of the First Workshop on Applications of Pattern Analysis (WAPA 2010): 1-3 September 2010, Cumberland Lodge, Windsor, UK. Massachusetts Institute of Technology (MIT) Press, 2010. p. 36-43 (JMLR Workshop and Conference Proceedings; Vol. 11).

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Automating News Content Analysis: An Application to Gender Bias and Readability

AU - Ali, Omar

AU - Flaounas, Ilias

AU - Bie, Tijl De

AU - Mosdell, Nick

AU - Lewis, Justin

AU - Cristianini, Nello

N1 - ISBN: 19387228 Publisher: JMLR: Workshop and Conference Proceedings Name and Venue of Conference: Workshop on Applications of Pattern Analysis (WAPA) Other identifier: 2001261

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N2 - In this article we present an application of text-analysis technologies to support social science research, in particular the analysis of patterns in news content. We describe a system that gathers and annotates large volumes of textual data in order to extract patterns and trends. We have examined 3.5 million news articles and show that their topic is related to the gender bias and readability of their content. This study is intended to illustrate how pattern analysis technology can be deployed to automate tasks commonly performed by humans in the social sciences, in order to enable large scale studies that would otherwise be impossible.

AB - In this article we present an application of text-analysis technologies to support social science research, in particular the analysis of patterns in news content. We describe a system that gathers and annotates large volumes of textual data in order to extract patterns and trends. We have examined 3.5 million news articles and show that their topic is related to the gender bias and readability of their content. This study is intended to illustrate how pattern analysis technology can be deployed to automate tasks commonly performed by humans in the social sciences, in order to enable large scale studies that would otherwise be impossible.

UR - http://www.cs.bris.ac.uk/Publications/pub_master.jsp?id=2001261

M3 - Conference Contribution (Conference Proceeding)

T3 - JMLR Workshop and Conference Proceedings

SP - 36

EP - 43

BT - Proceedings of the First Workshop on Applications of Pattern Analysis (WAPA 2010)

PB - Massachusetts Institute of Technology (MIT) Press

ER -

Ali O, Flaounas I, Bie TD, Mosdell N, Lewis J, Cristianini N. Automating News Content Analysis: An Application to Gender Bias and Readability. In Proceedings of the First Workshop on Applications of Pattern Analysis (WAPA 2010): 1-3 September 2010, Cumberland Lodge, Windsor, UK. Massachusetts Institute of Technology (MIT) Press. 2010. p. 36-43. (JMLR Workshop and Conference Proceedings).

Automating News Content Analysis: An Application to Gender Bias and Readability

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