Automatic prediction of gender, political affiliation, and age in Swedish politicians from the wording of their speeches - A comparative study of classifiability

The present study explores automatic classification of Swedish politicians and their speeches into classes based on personal traits-gender, age, and political affiliation-as a means for measuring a ...

[1]  Yiming Yang,et al.  A Comparative Study on Feature Selection in Text Categorization , 1997, ICML.

[2]  George M. Mohay,et al.  Gender-preferential text mining of e-mail discourse , 2002, 18th Annual Computer Security Applications Conference, 2002. Proceedings..

[3]  Arjun Mukherjee,et al.  Improving Gender Classification of Blog Authors , 2010, EMNLP.

[4]  Marco Wiering,et al.  Categorizing Children: Automated Text Classification of CHILDES files , 2008 .

[5]  Thorsten Joachims,et al.  Text Categorization with Support Vector Machines: Learning with Many Relevant Features , 1998, ECML.

[6]  Yasuhiro Tajima,et al.  Generating a set of rules to determine the gender of a speaker of a Japanese sentence , 2009 .

[7]  Alan F. Smeaton,et al.  Text Categorisation of Racist Texts Using a Support Vector Machine , 2004 .

[8]  Shlomo Argamon,et al.  Automatically Categorizing Written Texts by Author Gender , 2002, Lit. Linguistic Comput..

[9]  Stefan Kaufmann,et al.  Classifying Party Affiliation from Political Speech , 2008 .

[10]  Lutz Hamel,et al.  Comparing the Results of Support Vector Machines with Traditional Data Mining Algorithms , 2007, DMIN.

[11]  Hsinchun Chen,et al.  Gender Classification for Web Forums , 2011, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[12]  Shlomo Argamon,et al.  Political Leaning Categorization by Exploring Subjectivities in Political Blogs , 2008, DMIN.

[13]  Walter Daelemans,et al.  Using syntactic features to predict author personality from text , 2008 .

[14]  Shlomo Argamon,et al.  Vive la Différence! Text Mining Gender Difference in French Literature , 2009, Digit. Humanit. Q..

[15]  Shlomo Argamon,et al.  Mining the Blogosphere: Age, gender and the varieties of self-expression , 2007, First Monday.

[16]  Mari Ostendorf,et al.  A Quantitative Analysis of Lexical Differences Between Genders in Telephone Conversations , 2005, ACL.

[17]  Berkant Barla Cambazoglu,et al.  Chat Mining for Gender Prediction , 2006, ADVIS.

[18]  Moshe Koppel,et al.  Automatically Classifying Documents by Ideological and Organizational Affiliation , 2009, 2009 IEEE International Conference on Intelligence and Security Informatics.

[19]  Jahna Otterbacher,et al.  Inferring gender of movie reviewers: exploiting writing style, content and metadata , 2010, CIKM.

[20]  Jon Oberlander,et al.  The Identity of Bloggers: Openness and Gender in Personal Weblogs , 2006, AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs.

[21]  Scott Nowson.  The Language of Weblogs: A study of genre and individual differences , 2006 .

[22]  Stefan Kaufmann,et al.  Language and Ideology in Congress , 2011, British Journal of Political Science.

[23]  Hsinchun Chen,et al.  Gender difference analysis of political web forums: An experiment on an international islamic women's forum , 2009, 2009 IEEE International Conference on Intelligence and Security Informatics.

[24]  Mitsuru Ishizuka,et al.  Automatic Estimation of Bloggers' Gender , 2007, ICWSM.

[25]  Thorsten Joachims,et al.  Making large-scale support vector machine learning practical , 1999 .

[26]  Shlomo Argamon,et al.  Effects of Age and Gender on Blogging , 2006, AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs.

[27]  Jade Goldstein-Stewart,et al.  Gender Differences across Correlated Corpora: Preliminary Results , 2008, FLAIRS.