METHODS AND SYSTEMS FOR QUANTIFYING AND TRACKING SOFTWARE APPLICATION QUALITY

1 . A computer-implemented method for indicating quality of a software application, comprising the steps of:

capturing users reviews for the software application from a plurality of feedback sources;

analyzing the user reviews of the software application, wherein analyzing includes identifying signals in quality and classifying the user reviews into a plurality of quality attributes;

applying a weight to the plurality of quality attributes, wherein applying the weight includes deriving a respective weight from user reviews for other software applications;

determining a total score for the software application based on weighted scores for each of the plurality of quality attributes; and

presenting the weighted scores for each of the plurality of quality attributes for the software application.

2 . The method of claim 1 , wherein the act of capturing users reviews includes an act of crawling application reviews in at least one of application stores, media feeds, automated testing services, or crowd testing platforms.

3 . The method of claim 1 , further comprising an act of deriving a respective weight for a respective quality attribute based on analysis of aggregate reviews in respective categories.

4 . The method of claim 1 , wherein each user review is classified into the plurality of quality attributes based on the text of the user review, the length of the user review, or sentence structure in the user review.

5 . The method of claim 1 , wherein the plurality of quality attributes comprise accessibility, accuracy, availability, content, elegance, inter-operability, localization, performance, pricing, privacy, satisfaction, security, stability, or usability.

6 . The method of claim 1 , wherein the user reviews each include a rating score, rating text, device information, date/time of review, and software application version number.

7 . The method of claim 1 , wherein classifying each user review comprises analyzing substring matches, statistically improbable phrases, or n-grams, or by using machine learning.

8 . The method of claim 1 , further comprising determining a quality rank for the software application relative to other software applications in the same category.

9 . The method of claim 1 , further comprising tracking quality attributes or quality rank of the software application over a given period of time.

10 . The method of claim 1 , further comprising generating a user interface display including categories associated with software application, category weighting applied to each category, top score for applications in the categories, and score for the software application in the categories.

11 . A system for indicating quality of a software application, the system comprising:

at least one processor operatively connected to a memory, the at least one processor configured to:

capture users reviews for the software application from a plurality of feedback sources;

analyze the user reviews of the software application based on signal in quality;

classify the user reviews into a plurality of quality attributes;

apply a weight to the plurality of quality attributes, wherein applying the weight includes deriving a respective weight from user reviews for other software applications;

determine a total score for the software application based on weighted scores for each of the plurality of quality attributes; and

present the weighted scores for each of the plurality of quality attributes for the software application.

12 . The system of claim 11 , wherein the total score is based at least in part on a user rating score provided in each user review.

13 . The system of claim 11 , wherein the at least one processor is further configured to classify user reviews into the plurality of quality attributes based on the text of the user review, the length of the user review, or sentence structure in the user review.

14 . The system of claim 11 , wherein the plurality of quality attributes comprise accessibility, accuracy, availability, content, elegance, inter-operability, localization, performance, pricing, privacy, satisfaction, security, stability, or usability.

15 . The system of claim 11 , wherein the at least one processor is further configured to crawl application reviews in at least one of application stores, media feeds, automated testing services, or crowd testing platforms.

16 . The system of claim 11 , wherein the at least one processor is further configured to derive a respective weight for a respective quality attribute based on analysis of aggregate reviews in respective categories.

17 . The system of claim 1 , wherein the at least one processor is further configured to analyze substring matches, statistically improbable phrases, or n-grams, or employ machine learning, to classify user reviews.

18 . The system of claim 1 , wherein the at least one processor is further configured to determine a quality rank for the software application relative to other software applications in the same category.

19 . The system of claim 1 , wherein the at least one processor is further configured to track quality attributes or quality rank of the software application over a given period of time.

20 . The system of claim 1 , wherein the at least one processor is further configured to generate a user interface display including categories associated with the software application, category weighting applied to each category, top score for software applications in the categories, and a score for the software application in the categories.