Gender Prediction in English-Hindi Code-Mixed Social Media Content : Corpus and Baseline System

by   Ankush Khandelwal, et al.

The rapid expansion in the usage of social media networking sites leads to a huge amount of unprocessed user generated data which can be used for text mining. Author profiling is the problem of automatically determining profiling aspects like the author's gender and age group through a text is gaining much popularity in computational linguistics. Most of the past research in author profiling is concentrated on English texts 1,2. However many users often change the language while posting on social media which is called code-mixing, and it develops some challenges in the field of text classification and author profiling like variations in spelling, non-grammatical structure and transliteration 3. There are very few English-Hindi code-mixed annotated datasets of social media content present online 4. In this paper, we analyze the task of author's gender prediction in code-mixed content and present a corpus of English-Hindi texts collected from Twitter which is annotated with author's gender. We also explore language identification of every word in this corpus. We present a supervised classification baseline system which uses various machine learning algorithms to identify the gender of an author using a text, based on character and word level features.


page 1

page 2

page 3

page 4


Humor Detection in English-Hindi Code-Mixed Social Media Content : Corpus and Baseline System

The tremendous amount of user generated data through social networking s...

A visual approach for age and gender identification on Twitter

The goal of Author Profiling (AP) is to identify demographic aspects (e....

Vector Space Model as Cognitive Space for Text Classification

In this era of digitization, knowing the user's sociolect aspects have b...

Exploring difference in public perceptions on HPV vaccine between gender groups from Twitter using deep learning

In this study, we proposed a convolutional neural network model for gend...

Characterizing the Google Books corpus: Strong limits to inferences of socio-cultural and linguistic evolution

It is tempting to treat frequency trends from the Google Books data sets...

An English-Hindi Code-Mixed Corpus: Stance Annotation and Baseline System

Social media has become one of the main channels for peo- ple to communi...

Normalization of Transliterated Words in Code-Mixed Data Using Seq2Seq Model & Levenshtein Distance

Building tools for code-mixed data is rapidly gaining popularity in the ...

Please sign up or login with your details

Forgot password? Click here to reset