Automating Quantitative Narrative Analysis of News Data

Saatviga Sudhahar, Roberto Franzosi, Nello Cristianini
Proceedings of the Second Workshop on Applications of Pattern Analysis, PMLR 17:63-71, 2011.

Abstract

We present a working system for large scale quantitative narrative analysis (QNA) of news corpora, which includes various recent ideas from text mining and pattern analysis in order to solve a problem arising in computational social sciences. The task is that of identifying the key actors in a body of news, and the actions they perform, so that further analysis can be carried out. This step is normally performed by hand and is very labour intensive. We then characterise the actors by: studying their position in the overall network of actors and actions; studying the time series associated with some of their properties; generating scatter plots describing the subject/object bias of each actor; and investigating the types of actions each actor is most associated with. The system is demonstrated on a set of 100,000 articles about crime appeared on the New York Times between 1987 and 2007. As an example, we find that Men were most commonly responsible for crimes against the person, while Women and Children were most often victims of those crimes.

Cite this Paper

BibTeX
@InProceedings{pmlr-v17-sudhahar11a, title = {Automating Quantitative Narrative Analysis of News Data}, author = {Sudhahar, Saatviga and Franzosi, Roberto and Cristianini, Nello}, booktitle = {Proceedings of the Second Workshop on Applications of Pattern Analysis}, pages = {63--71}, year = {2011}, editor = {Diethe, Tom and Balcazar, Jose and Shawe-Taylor, John and Tirnauca, Cristina}, volume = {17}, series = {Proceedings of Machine Learning Research}, address = {CIEM, Castro Urdiales, Spain}, month = {19--21 Oct}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v17/sudhahar11a/sudhahar11a.pdf}, url = {https://proceedings.mlr.press/v17/sudhahar11a.html}, abstract = {We present a working system for large scale quantitative narrative analysis (QNA) of news corpora, which includes various recent ideas from text mining and pattern analysis in order to solve a problem arising in computational social sciences. The task is that of identifying the key actors in a body of news, and the actions they perform, so that further analysis can be carried out. This step is normally performed by hand and is very labour intensive. We then characterise the actors by: studying their position in the overall network of actors and actions; studying the time series associated with some of their properties; generating scatter plots describing the subject/object bias of each actor; and investigating the types of actions each actor is most associated with. The system is demonstrated on a set of 100,000 articles about crime appeared on the New York Times between 1987 and 2007. As an example, we find that Men were most commonly responsible for crimes against the person, while Women and Children were most often victims of those crimes.} }
Endnote
%0 Conference Paper %T Automating Quantitative Narrative Analysis of News Data %A Saatviga Sudhahar %A Roberto Franzosi %A Nello Cristianini %B Proceedings of the Second Workshop on Applications of Pattern Analysis %C Proceedings of Machine Learning Research %D 2011 %E Tom Diethe %E Jose Balcazar %E John Shawe-Taylor %E Cristina Tirnauca %F pmlr-v17-sudhahar11a %I PMLR %P 63--71 %U https://proceedings.mlr.press/v17/sudhahar11a.html %V 17 %X We present a working system for large scale quantitative narrative analysis (QNA) of news corpora, which includes various recent ideas from text mining and pattern analysis in order to solve a problem arising in computational social sciences. The task is that of identifying the key actors in a body of news, and the actions they perform, so that further analysis can be carried out. This step is normally performed by hand and is very labour intensive. We then characterise the actors by: studying their position in the overall network of actors and actions; studying the time series associated with some of their properties; generating scatter plots describing the subject/object bias of each actor; and investigating the types of actions each actor is most associated with. The system is demonstrated on a set of 100,000 articles about crime appeared on the New York Times between 1987 and 2007. As an example, we find that Men were most commonly responsible for crimes against the person, while Women and Children were most often victims of those crimes.
RIS
TY - CPAPER TI - Automating Quantitative Narrative Analysis of News Data AU - Saatviga Sudhahar AU - Roberto Franzosi AU - Nello Cristianini BT - Proceedings of the Second Workshop on Applications of Pattern Analysis DA - 2011/10/21 ED - Tom Diethe ED - Jose Balcazar ED - John Shawe-Taylor ED - Cristina Tirnauca ID - pmlr-v17-sudhahar11a PB - PMLR DP - Proceedings of Machine Learning Research VL - 17 SP - 63 EP - 71 L1 - http://proceedings.mlr.press/v17/sudhahar11a/sudhahar11a.pdf UR - https://proceedings.mlr.press/v17/sudhahar11a.html AB - We present a working system for large scale quantitative narrative analysis (QNA) of news corpora, which includes various recent ideas from text mining and pattern analysis in order to solve a problem arising in computational social sciences. The task is that of identifying the key actors in a body of news, and the actions they perform, so that further analysis can be carried out. This step is normally performed by hand and is very labour intensive. We then characterise the actors by: studying their position in the overall network of actors and actions; studying the time series associated with some of their properties; generating scatter plots describing the subject/object bias of each actor; and investigating the types of actions each actor is most associated with. The system is demonstrated on a set of 100,000 articles about crime appeared on the New York Times between 1987 and 2007. As an example, we find that Men were most commonly responsible for crimes against the person, while Women and Children were most often victims of those crimes. ER -
APA
Sudhahar, S., Franzosi, R. & Cristianini, N.. (2011). Automating Quantitative Narrative Analysis of News Data. Proceedings of the Second Workshop on Applications of Pattern Analysis, in Proceedings of Machine Learning Research 17:63-71 Available from https://proceedings.mlr.press/v17/sudhahar11a.html.

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