Detecting Twitter users' gender, en francais

November 28, 2013 by Chris Chipello

With 230 million users, Twitter has become a global force in social media. And not just in English.

Data miners have been hard at work trying to figure out the attributes of Twitter users – such as gender and age—that aren't explicitly revealed on Twitter feeds. That information could be hugely valuable to marketers, enabling them to target messages to their desired audience. Nearly all the research done so far, however, has focused on English users and content.

Now, a McGill University research team has conducted one of the first studies designed to figure out the gender of Twitter users who primarily use languages other than English.

Among the key findings: by using a special detector based on French-language syntax, the researchers showed that it is very easy to classify gender for Twitter users in French – and probably for other Romance languages. In particular, the researchers developed an algorithm to look for masculine or feminine adjectives or past participles following the phrase "Je suis" (or variants such as "je ne suis pas").

Based on this construction, the detector was able to determine the gender of users with 90% accuracy – significantly higher than the accuracy rates of 80% to 85% achieved by various algorithms that have been developed to analyze English-language content.

Because French adjectives and past participles have masculine and feminine forms that are often spelled differently, "You don't have to get too fancy" to develop an effective gender detector for Tweets in the language, says Derek Ruths, a McGill computer-science professor who co-authored the study.

Since most individuals include photos of themselves on their Tweets, identifying male and female users might seem as simple as looking at the photos. But sorting through hundreds of millions of tweets is a task for computers, and "computers aren't good at looking at pictures," Ruths notes.

The McGill study was presented at a recent international conference in Seattle organized by the Association for Computational Linguistics. The paper also examines Twitter data sets for Japanese, Indonesian and Turkish. Japanese proved to be the toughest for inferring .

The results obtained for French show that some languages have features better suited for certain classification tasks. "Identifying and leveraging such features promises to be an interesting and effective direction for future work," adds McGill linguistics professor Morgan Sonderegger, who co-authored the paper with Ruths and computer-science undergraduate student Morgane Ciot.

Explore further: Twitter plans French, German, Italian and Spanish sites

More information: Link to the paper: www.derekruths.com/static/publication_files/CiotSondereggerRuths_EMNLP2013.pdf
Link to the conference website: hum.csse.unimelb.edu.au/emnlp2013/

Related Stories

Twitter clocks half-billion users: monitor

July 30, 2012

Over 500 million people are on micro-blogging site Twitter and Americans and Brazilians are the most connected, according to a study by social media monitor Semiocast released Monday.

Recommended for you

Inferring urban travel patterns from cellphone data

August 29, 2016

In making decisions about infrastructure development and resource allocation, city planners rely on models of how people move through their cities, on foot, in cars, and on public transportation. Those models are largely ...

How machine learning can help with voice disorders

August 29, 2016

There's no human instinct more basic than speech, and yet, for many people, talking can be taxing. 1 in 14 working-age Americans suffer from voice disorders that are often associated with abnormal vocal behaviors - some of ...

Apple issues update after cyber weapon captured

August 26, 2016

Apple iPhone owners on Friday were urged to install a quickly released security update after a sophisticated attack on an Emirati dissident exposed vulnerabilities targeted by cyber arms dealers.

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.