Evaluating the Effective Factors on Eating Disorders Prevention Methods Using Analysis of Food-Related Data on Twitter

Eating disorders are making a point of challenge for health-related researches. Using big data for this type of researches can effectively help researchers use a beneficial resource of information worldwide in real-time. This study aimed to introduce a more accurate method for analyzing food-related data and making relations between peoplechr(chr(chr('39')39chr('39'))39chr(chr('39')39chr('39')))s opinions and the prevention treatments (for eating disorders), which can be applied to any country.

In this data mining study, more than 2 million eating-related tweets were collected from Twitter and analyzed by novel methods for big data research on eating disorders and other present Twitter analysis methods.

Many factors such as age, location, gender, and their combination were discussed as effective factors in eating disorders. Eleven countries were selected to discuss the rate of eating disorders and location-related prevention methods.

Some factors such as location and age are effective indicators. Some combinations of factors are also considered influencing indicators when applied together, such as gender+age, gender+location, and gender+age+location.