# Understanding Developers Privacy Concerns Through Reddit Thread Analysis

**Authors:** Jonathan Parsons, Michael Schrider, Oyebanjo Ogunlela, Sepideh Ghanavati  
**arXiv:** [2304.07650](https://arxiv.org/abs/2304.07650)  
**Date:** 2023-04-15  
**Summary page:** https://www.summarizepaper.com/en/arxiv-id/2304.07650v1/

## Key points

- Developing applications with user privacy in mind is increasingly important
- Researchers from the University of Maine analyzed discussions on Reddit forums related to web and mobile development to understand developer perceptions and challenges
- Natural Language Processing (NLP) was used on 437,317 threads from subreddits such as r/webdev, r/androiddev, and r/iOSProgramming
- Simple phrase frequency analysis and Latent Dirichlet Allocation (LDA) were used to identify common points of discussion and topics that change over time as new regulations are passed around the globe
- Adaptive Boosting (AdaBoost) models were used to classify posts in their dataset as questions
- Through LDA analysis, ten topics for posts pre- and post-GDPR and pre- and post-CCPA were generated
- Sentiment analysis using Natural Language Toolkit (NLTK) approaches was also performed
- Common trends in privacy topics among different subreddits were found while the frequency of those topics differs between web and mobile applications
- Developers discuss concerns related to unique identifiers such as social security numbers or online identifiers like usernames or email addresses
- They also discuss issues related to data categories such as photos/videos, audio recordings/voice, location information/physical address
- The study provides valuable insights into how developers perceive privacy-related challenges while developing applications
- Understanding these perceptions can help inform future policy decisions related to data protection regulations
- It can also guide developers towards best practices when it comes to designing applications with user privacy in mind.

## Summary

In today's privacy-focused world, developing applications with user privacy in mind is becoming increasingly important. To better understand the perceptions and challenges of developers in this space, a team of researchers from the University of Maine conducted a study analyzing discussions on Reddit forums related to web and mobile development. The team used various forms of Natural Language Processing (NLP) on 437,317 threads from subreddits such as r/webdev, r/androiddev, and r/iOSProgramming to identify common points of discussion and how they change over time as new regulations are passed around the globe. To answer their research questions, the team conducted simple phrase frequency analysis and identified topics using Latent Dirichlet Allocation (LDA). They also used Adaptive Boosting (AdaBoost) models to classify posts in their dataset as questions. Through LDA analysis, they generated ten topics for posts pre- and post-GDPR and pre- and post-CCPA. The team also performed sentiment analysis using Natural Language Toolkit (NLTK) approaches. Their results show that there are common trends in privacy topics among different subreddits while the frequency of those topics differs between web and mobile applications. They found that developers discuss concerns related to unique identifiers such as social security numbers or online identifiers like usernames or email addresses. They also discuss issues related to data categories such as photos/videos, audio recordings/voice, location information/physical address. The team's study provides valuable insights into how developers perceive privacy-related challenges while developing applications. By understanding these perceptions, it can help inform future policy decisions related to data protection regulations. Additionally, it can help guide developers towards best practices when it comes to designing applications with user privacy in mind.