2. Objectives
•The objectives of the project include detecting gender of the
person using social media data
•We analyzed data from multiple machine learning projects
to find out the possible machine learning techniques that
can be used
Aim: Gender Prediction Using
Machine Learning Methods
3. Gender Prediction Using machine Learning
Techniques
• Scope: Machine learning technology has enabled us to answer questions
that were difficult to answer before. By using appropriate classification
machine learning technique, we can surely answer this question of gender
prediction
• Research design: We can use classification algorithm to predict the gender
of the person which will further enable us to apply this application to
other areas as well. Algorithms like Decision Trees, Random Forest can be
used
• Management: The project will be completed in the given time frame and its
goal will be achieved successfully.
4. Actual Problem
• Gender prediction plays a foundational role in many of the concepts like
military enforcements, access control, market intelligence, machine -human
interaction and so on
• So to predict the gender of a person for multiple purposes remains a
problem that needs to be solved
• There is requirement of gender prediction in social media platforms and
new technologies needs to be implemented to perform these predictions
5. Context Literature
We have reviewed various papers and journals and tried to assess papers.
Some of them are listed as below:
• Liu, C., Li, F. And li, L. (2021). Research on gender prediction for social
media user profiling by machine learning method. 2021 international
conference on communications, information system and computer
engineering (CISCE). Doi:10.1109/cisce52179.2021.9445922.
•
• Delgado helleseter, m., Kuhn, P.J. And shen, K. (2016). Age and gender
profiling in the chinese and mexican labor markets: evidence from four
job boards. SSRN electronic journal. Doi:10.2139/ssrn.2769199.
6. Research Design
To predict gender using machine
learning techniques
• The data that will be used in
the program will be taken
from social media sites like
twitter or facebook.
• Or we might use secondary
data sources like kaggle to
collect the data
Start
Data
collection
Data Pre-
processing
Features
Extraction
ML
algorithm
Result
Assessment
Finish
7. Approach to data collection
• Data will be in the form of social media comments like the user posts on
social media platform like twitter
• It will be raw contextual data that will be processed further to solve the
problem
• Data will be divided into various parameters and feature extraction will be a
crucial process
8. Ethical and practical considerations
• We are getting the desired result to predict the persons gender on the
basis of the data
• This project has various applications like can be used by ad companies to
target the particular audience and play relevant type of ads according to
gender
• Various social media aspects and applications will find this application
useful
9. Evaluation
• The studies result can be evaluated and results can be compared with
different models for accuracy.
• Also, it has various applications like it can be used by ad agencies
• Human gender classification is an emerging technology that can be used by
companies to target a particular set of audience based on gender
10. Plan
The time that has been allocated to me, I will try to break the time
systematically so that we can practically achieve our goals. Further literature
review, collection of data and evaluation of data needs to be done. Validation
of conclusions is necessary. Also, taking feedback of supervisors will also be
part of the process. Also the evaluation and systematic performance
assessment will also be taken care of.
