JBeukema
Rookie
- Banned
- #1
In 2003, a team of researchers from the Illinois Institute of Technology and Bar-Ilan University in Israel (Shlomo Argamon, Moshe Koppel, Jonathan Fine, and Anat Rachel Shimoni) developed a method to estimate gender from word usage. Their paper described a Bayesian network where weighted word frequencies and parts of speech could be used to estimate the gender of an author. Their approach made a distinction between fiction and non-fiction writing styles. A simplified version of this work was implemented as the Gender Genie. They showed that fewer words were needed and that writing styles varied based on the forum. For example, fiction and non-fiction differs from blogs (informal writing). Even though the genres differ, there are still gender-specific word frequencies.
This Gender Guesser system is heavily based on the Gender Genie. In particular, the word lists and weights are reproduced from the Gender Genie. The Gender Guesser extends the interpretation of informal writing to work on blogs and chat-room messages, and combines formal writing styles (fiction, non-fiction, essays, news reports, etc.). It also looks for weak emphasis -- used to distinguish European English from American English. In general, if the difference between male and female weight values is not significant (a "weak" score), then the author could be European. This is because the weight matrix is biased for distinguishing genders in American English.
Gender Guesser
Results for The Red Republic:
Total words: 326
Genre: Informal
Female = 191
Male = 710
Difference = 519; 78.8%
Verdict: MALE