WhatsApp is one of the largest social media and messaging platforms in the world. It securely connects friends and family across international borders and enables easy communication. However, these aspects of WhatsApp are what also allow misinformation to spread across the platform. Other social media platforms with publicly facing data contain valuable information that allows its users to understand the origins and intent of a post such as where it originated, when it was posted, how many times it has been viewed, and content warnings. Fundamentally, WhatsApp cannot display this information due to its encryption.

My service will solve this ambiguity behind messages. It will allow users access to this crucial information necessary to analyze their messages and gain a deeper understanding of the intent behind the received messages.

The best thing we can do to combat misinformation is to arm internet users with the tools needed to make an informed decision about the context the consume.

My solution is natural approach to. Using the Twilio WhatsApp API, my service will be linked to a WhatsApp number. Just as easily as users can forward messages to their friends, they can forward messages they want to analyze to my service’s WhatsApp number. Forwarding the message will initiate a full analysis of the message.

Everything from media (images, video, audio, PDFs), message text, links to YouTube videos, and even links to other websites can be analyzed.

In seconds, the message is analyzed, and the user will receive a reply message that contains information about the message being queried. Information like when the message was first sent, origin location, countries where the message is most prevalent, content warnings, and even message translation – this information is vital to understanding the intent behind a message and helps users make informed decisions about the message they are analyzing.

Detailed reports can be generated for YouTube Videos with content warnings for life-threatening and important topics

Detailed reports can be generated for Text Messages

Identification and detailed reporting also works for media files like images, video, and audio records

NSF I-Corps Grant:

I recently received a grant to continue developing this application and explore commercialization opportunities.

Website:

In addition to a forwarding Service, development will also begin for a website that users can visit to get more information about the message and its contents. Through this website, users can join a discussion about the message, see expert opinions on the topic matter and even rate the message.

By providing an intuitive service to not only receive valuable data about a message’s origins but also provide a platform to get informed and in-depth details about messages, my service will directly combat misinformation on WhatsApp.

Whats App Service:

Provide More In-depth analysis with more accurate reports

Bugs Noticed:

Pertaining to the WhatsApp sandbox:

According to the documentation incoming messages longer than 1600 characters are "will be truncated to 1600 characters, and will be marked as failed with Error 21617." Click Here for Documentation

However, when working with the WhatsApp Sandbox, messages longer than 1600 characters are never delivered and no post request is sent to the application.

This is an important thing to look at as many messages sent on WhatsApp are long (usually more than 1600 characters) and having the ability to develop for it in the Sandbox will be very useful.