Study reveals how you behave on the internet is influenced by your income level

A research collaboration between Vahid Ghafouri and Guillermo Suárez de Tangil from IMDEA Networks Institute, along with Waleed Iqbal, Gareth Tyson, and Ignacio Castro from Queen Mary University of London, explores the ways in which real-world inequalities are reflected in social networks.

Their study, titled “Lady and the Tramp Nextdoor: Online Manifestations of Real-World Inequalities in the Nextdoor Social Network,” was presented at the ICWSM 2023 conference. The research reveals that a person’s income level influences the type of content they share online.

The researchers analyzed 2.6 million posts from 64,283 areas in the U.S. and 3,325 neighborhoods in the U.K. published on NextDoor, a social network where users discuss problems in their neighborhoods. By examining the locations attached to each post, the researchers estimated the users’ income based on the average income of those locations provided by the governments.

The analysis showed that individuals residing in wealthier neighborhoods tend to participate in discussions about crime more frequently than those in poorer neighborhoods. This observation suggests that there may be a need for policymakers to pay more attention to crime issues and allocate resources accordingly.

Vahid Ghafouri, a Ph.D. student at IMDEA Networks and UC3M and co-author of the study, stated, “Surprisingly, this pattern persists despite the fact that real crime rates are lower in wealthier neighborhoods. This suggests that rich people are more sensitive and reactive to the presence of crime.”

The research also revealed that nonviolent crimes were discussed more than violent ones by both Americans and British users. However, wealthy Americans focused more on violent crime and weapons compared to their counterparts in the U.K.

Additionally, the study found that residents of wealthier neighborhoods expressed more positive sentiments in their online texts, indicating a potential correlation between income and happiness. This trend was consistent across both the U.S. and the U.K.

This groundbreaking research showcases the potential of AI and Natural Language Processing in predicting income, inequality, and crime rates based on user-generated online content. It has been published in the Proceedings of the International AAAI Conference on Web and Social Media.

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