Gender Classification of Weblog Authors
78 citations recorded by the source corpus.
Subfields: Natural Language Processing, Sentiment & Opinion Analysis
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Natural Language Processing
- Anna Rohrbach
- Lisa Anne Hendricks
- Trevor Darrell
- Kaylee Burns
- Dong Nguyen
- Sara Rosenthal
- Franciska de Jong
- B. Liu
In Sentiment & Opinion Analysis
- Franciska de Jong
- Dong Nguyen
- B. Liu
- Brian N. Larson
- A. Seza Doğruöz
- Carolyn Penstein Rosé
- Arjun Mukherjee
- Bing Liu
Citations in the corpus
- Women also Snowboard: Overcoming Bias in Captioning Models (2018, background): “Gender classification has also been studied in natural language processing ([41,42], [43]).”
- Gender as a Variable in Natural-Language Processing: Ethical Considerations (2017, background): “For example, two early studies, Yan and Yan (2006) and Argamon et al. (2007), used machine learning to classify blogs by their authors’ genders.”
- Obfuscating Gender in Social Media Writing (2016, background): “, 2015), weblogs (Mukherjee and Liu, 2010; Schler et al., 2006; Yan and Yan, 2006) and user-review sites (Johannsen et al.”
- Age Prediction in Blogs: A Study of Style, Content, and Online Behavior in Pre- and Post-Social Media Generations (2011, background): “Other researchers have investigated weblogs for differences in writing style depending on gender identification (Herring and Paolillo, 2006; Yan and Yan, 2006; Nowson and Oberlander, 2006).”
- Stylometric Analysis of Bloggers' Age and Gender (2009, background): “Analyses of effects of bloggers’ age and gender from weblogs have been presented by a few (Schler et al. 2006; Burger and Henderson 2006; Yan 2006 ; Argamon, Koppel and Avneri 1998; Yan and Yan 2006; Nowson and Oberlander 2006) but as per our analysis these are generally based on usage of keywords, ”
- Improving Gender Classification of Blog Authors (2010, methodology): “…work has also attempted gender classification of blog authors using features such as content words, dictionary based content analysis results, POS (part-of-speech) tags and feature selection along with a supervised learning algorithm (Schler et al., 2006; Argamon et al., 2007; Yan and Yan, 2006).”
- Computational Sociolinguistics: A Survey (2016, methodology): “Others have created their own blog corpus from various sources including LiveJournal and Xanga (Burger and Henderson 2006; Mukherjee and Liu 2010; Nowson and Oberlander 2006; Rosenthal and McKeown 2011; Sarawgi, Gajulapalli, and Choi 2011; Yan and Yan 2006).”