Popular Prediction with Information and Features

Information Technology

Social media platforms have democratized the process of web content creation allowing mere consumers to become creators and distributors of content. But this has also contributed to an explosive growth of information and has intensified the online competition for user’s attention, since only a small number of items become popular while the rest remain unknown. Understanding what makes one item more popular than another, observing its popularity dynamics, and being able to predict its popularity has thus attracted a lot of interest in the past few years. In this work, we are predicting popular places which are worth visiting, and unpopular places with their comments using machine learning algorithms, we have also integrated google maps to find nearby places, coffee shops, ATMs, malls etc. Predicting the popularity of web content is useful in many areas such as network dimensioning, online marketing or real-world outcome prediction.

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