Abstract: System, method, and computer program product (e.g. mobile App) and/or web-based service to enable users to research reviews written online to assess the performance and functionality of mobile applications. The system extracts reviews from multiple online sources comprising: mobile Apps “stores”, blogs, online magazines, websites, etc.; and, utilizes sentiment analysis algorithms and supervised machine learning analysis to present more informative summaries for each App's reviews. Summaries may comprise: a sentence that encapsulates a sentiment held by many users; the most positive and negative comments; and a list of features with average scores (e.g. graphics, fun, easy to use, etc.). Additionally, the user may view a separate review detail page per App that provides further summaries, such as a short list of other Apps that the same reviewer gave a very positive review for the features. The user is then able to purchase and download the App via a link.

Abstract: System, method, and computer program product for researching reviews written online to assess the performance and functionality of digital media consumer products bought online or not (e.g. eBooks, movies, TV shows, music, DVD's, etc.). The system extracts reviews from multiple online sources comprising: online “stores”, professional articles, blogs, online magazines, websites, etc.; and, utilizes sentiment analysis algorithms and supervised machine learning analysis to present more informative summaries for each product's reviews, comprising: a sentence that encapsulates a sentiment held by many users; the most positive and negative comments; and a list of features with average scores (e.g. performance, price, etc.). Additionally, the user may view a separate review detail page per product that provides further summaries, such as a short list of other products that the same reviewer gave a very positive review for the features. The user is then able to purchase the product via a link.