A Stochastic Model for Estimating the Number of Offenders and Targets on Snapchat Platform

TL;DR

This paper introduces a stochastic model to estimate the total number of offenders and targets on Snapchat by analyzing reporting probabilities, addressing underreporting issues in social platform safety assessments.

Contribution

It presents a novel stochastic approach to estimate unseen offenders and targets on Snapchat based on reporting behavior, improving understanding of platform safety.

Findings

Estimated the total number of offenders and targets on Snapchat.

Quantified reporting probabilities for unsafe interactions.

Provided a framework for assessing platform safety more accurately.

Abstract

Snapchat, like many other social platforms, provides mechanisms for its users to report content and private/public interactions that violate their sense of safety and decency. From our experience and common sense, we can safely assume that not everybody makes an effort to report, leaving potentially a large number of offending users and content unnoticed. The goal of this work is to directly estimate the probability of someone reporting on Snapchat using current in-app reporting options and, thereby, to provide estimates of the total prevalence (count) of offenders and users subjected to their unwanted, unwelcome or unsafe interactions.