Citation

Material Information

Title:
Web Traffic: Finding links in social media and human trafficking
Creator:
Romero, Jose M.
Kittelson, David
Griffin, Stuart
Place of Publication:
Denver, CO
Publisher:
Metropolitan State University of Denver
Publication Date:

Subjects

Genre:
Conference Papers ( sobekcm )

Notes

Acquisition:
Collected for Auraria Institutional Repository by the Self-Submittal tool. Submitted by Matthew Mariner.
General Note:
Faculty mentors: Thyago Mota, Steven Beaty
General Note:
Major: Computer science

Record Information

Source Institution:
Auraria Institutional Repository
Holding Location:
Auraria Library
Rights Management:
All applicable rights reserved by the source institution and holding location.

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Web Traffic: Finding links in social media and human trafficking Introduction: This project aims to stop human trafficking by taking data from the clear net, more specifically through WhatsApp. WhatsApp is a messaging app owned by Facebook. We are mostly focusing on groups that are in Brazil and Mexico. Monce Romero Advisor: Dr. Mota & Dr. Beaty Background: WhatsApp In order to be able to collect data from WhatsApp, we first needed to join WhatsApp groups. There are open groups (public) and closed groups (private groups that are only by invitation). We used Scrapy (which is a bot) to scrape the data from the websites that have WhatsApp groups. Using the same tool we can then create an excel file that contains all the data like the link to get into the WhatsApp group and a description of the group. Future Development: Filter through all the WhatsApp groups that we have collected and be able to get rid of the emojis within the file. Implement machine learning algorithm within our scrapping tool to bypass "Captchas". Questions? Email me at jromer97@msudenver.edu Collaborating with David Kittleson, Anna Sanchez, Stuart Griffin. Process 1. Executing the Program 2. New File being added 3. Data Conclusion: The main purpose of this project is to contribute to our society by trying to stop human trafficking by understanding the TOR network and WhatsApp. Results: Once we are done scrapping the data and adding some contents within the data, we have around 3000 different WhatsApp groups to join. This will allow us to collect data directly within these groups.