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Scientists Can Predict A Person’s Income Based Only On Social Media Posts

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Scientists Can Predict A Person's Income Based Only On Social Media Posts

The social media posts can indicate socioeconomic level, with wealthier areas exhibiting more positive but crime-sensitive messages, according to a large-scale research utilizing 2.6 million Nextdoor posts. The study also reveals variations in the manner in which crime is discussed, with wealthier regions in both the US and the UK discussing it more frequently while having lower actual crime rates and talks in the US being more heavily weighted towards violent crimes and firearms.

Researchers at Queen Mary University of London examined 2.6 million social media posts on the popular platform Nextdoor as part of their study. Unexpectedly, they could properly forecast a person’s income based just on the content of their posts.

The researchers found significant differences in the material shared by people living in more affluent neighborhoods and those who live in less affluent neighborhoods. This finding raises the possibility of user profiling by raising the likelihood that our entire online behaviors, not just those on Nextdoor, may provide information about our socioeconomic status.

Social media posts could be able to propose material to users based on their income if they are aware of their person’s income . Additionally, marketers and e-commerce companies might utilise this economic profiling to better target consumers. They do so by  marketing particular items at various price points in accordance with the user’s income level.

Scientists Can Predict A Person's Income Based Only On Social Media Posts
Scientists Can Predict A Person’s Income Based Only On Social Media Posts

The study’s results also revealed that even if crime rates in wealthy neighborhoods are lower than in poorer ones, residents there were more inclined to share positive postings and talk about crime more.

Our work demonstrates that the social media posts submitted by users in underprivileged neighborhoods can be distinguished from the material produced in wealthy neighborhoods, according to Dr. Ignacio Castro, main researcher and Lecturer in Data Analytics at Queen Mary University of London. Online users’ content reflects socioeconomic factors: more crime-sensitive posting occurs in affluent neighborhoods, but generally, the attitude in the posts is more positive.

This is the first extensive examination of Nextdoor that demonstrates how income levels and economic disparity within neighborhoods emerge online. It was published on June 2 in the Proceedings of the International AAAI Conference on Web and Social Media. Between November 2020 and September 2021. 2.6 million Nextdoor postings from 64,283 American neighborhoods and 3,325 British neighborhoods were gathered and examined by researchers. The network, which boasts 10 million members, enables verified locals to contribute content on neighborhood-specific forums. The study’s findings are comparable in both nations.

The 20% richest neighborhoods talk about crime around 1.5 times more than the worst neighborhoods, indicating that residents in wealthier neighborhoods are more worried about crime. This occurs despite the fact that such impoverished areas have 1.3 times higher crime rates. More than anybody else, those who reside in affluent areas with less disparity talk about crime.

Non-violent crimes are addressed more frequently than violent crimes when it comes to the types of crimes that are discussed. There is one noticeable difference between user content patterns in the US and the UK when it comes to guns and violent crimes, which are talked about more in the US than in the UK for the wealthier neighborhoods. This differs from the situation in middle-class areas, where people tend to post more about this kind of violence than Americans do.

LinkedIn Is Planning To Employ Generative AI More Often To Create And Publish Content

READ ALSO – LinkedIn Is Planning To Employ Generative AI More Often To Create And Publish Content

LinkedIn is currently developing a new tool that will let users publish content using generative AI. The AI chatbot will produce an early draft of the user’s post based on the minimum of 30 words that the user provides defining its primary concept.

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