Tweets Can Be Analyzed To Determine Public Health Trends

Twitter‘s data has been used in the past to procure some very useful information and trends. Now, a study says that this data can be analyzed to reveal the current public health trends.


In order to determine a valid health trend in a country, one will need to take random samples of tweets from people in different parts of that country. This would help establish a good sample space and the tweets will then cough up such health trends and public health predictions which apply to most of the people.

Aron Culotta is a part of the research team who has decided to use the micro-blogging website for the said purpose. According to him, he collected 4.3 million tweets from people in 100 counties of U.S. These tweets underwent a linguistic analysis which revealed certain behaviors and habits.

According to Culotta, “For example, references to religion and certain pronouns (“we”, “her”) correlate with better socio-emotional support. References to money and inhibition correlate with lower unemployment. References to family and love correlate with higher rates of teen births. For obesity, indicators include what are known as Negative Engagement words (e.g., “tired”, “bored”, “sleepy”), as well as profanity.”

This is certainly a very interesting way of finding trends among tweets which otherwise seem normally worded. Culotta stresses on the importance of Twitter as a medium when he says, “Twitter activity provides a more fine-grained representation of a community’s health than demographics alone. The reason for this appears to come from the insights Twitter provides into personality, attitudes, and behavior, which in turn correlate with health outcomes.”

This is not the first time researchers have decided to use Twitter for health-related issues. In the past, data from Twitter has been used to track the outspread of epidemics in different parts of the world.

Courtesy: Pop Sci

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Salman Latif is a software engineer with a specific interest in social media, big data and real-world solutions using the two.Other than that, he is a bit of a gypsy. He also writes in his own blog. You can find him on Google+ and Twitter .

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