Multi-dimensional credibility scoring
View Patent ↗A credibility scoring system produces a multi-dimensional entity credibility score that is derived from multiple dimensional component scores. The credibility scoring system derives each dimensional component score from a different set of credibility data pertaining to different dimensional aspect of overall credibility. The different dimensional aspects factoring into the overall credibility determination include a stability dimension, transparency dimension, trustworthiness dimension, and sentiment dimension.
1. A computer-implemented method performed by a credibility score system, the computer-implemented method for generating a multi-dimensional credibility score, the computer-implemented method comprising:
with at least one machine of the credibility score system operating via a processor and non-transitory computer-readable memory:
aggregating from a plurality of data sources, a plurality of credibility data that impacts credibility of a particular entity;
classifying the plurality of credibility data according to first, second, and third credibility dimensions, said classifying comprising grouping a first subset of the plurality of credibility data to the first credibility dimension, a second subset of the plurality of credibility data to the second credibility dimension, and a third subset of the plurality of credibility data to the third credibility dimension, wherein each of the first, second, and third subsets comprises different credibility data;
producing a first component score based on the first subset of the plurality of credibility data, a second component score based on the second subset of the plurality of credibility data, and a third component score based on the third subset of the plurality of credibility data; and
generating an overall credibility score for the particular entity from the first component score, the second component score, and the third component score.
2. The computer-implemented method of claim 1 further comprising presenting credibility of the particular entity by presenting the overall credibility score with the first, second, and third component scores.
3. The computer-implemented method of claim 1 , wherein producing the first component score comprises generating a raw component score based on the first subset of the plurality of credibility data and generating a relative component based on a clustering of the particular entity's raw component score with raw component scores of other entities for the first dimension.
4. The computer-implemented method of claim 1 , wherein the first subset of the plurality of credibility data comprises sentiment data relating to opinions that others have expressed about the particular entity, the second subset of the plurality of credibility data comprises stability data accounting for historical performance of the particular entity, and the third subset of the plurality of credibility data comprises transparency data demonstrating the particular entity's presence online.
5. The computer-implemented method of claim 1 , wherein the first subset of the plurality of credibility data comprises reviews and ratings that are directed to the particular entity, the second subset of the plurality of credibility data comprises historical data about the particular entity, and the third subset of the plurality of credibility data comprises identifying information about the particular entity's presence online.
6. The computer-implemented method of claim 5 , wherein said classifying further comprises grouping a fourth subset of the plurality of credibility data to a fourth credibility dimension, the fourth subset of the plurality of credibility data relating to trustworthiness of the particular entity.
7. The computer-implemented method of claim 1 further comprising storing the overall credibility score, the first, second, and third component scores, and the first, second, and third subsets of the plurality of credibility data to the non-transitory computer-readable memory for subsequent access in response to a query for the credibility of the particular entity.
8. The computer-implemented method of claim 1 further comprising generating a report to detail the credibility of the particular entity by populating the report with the overall credibility score, the first, second, and third component scores, and the first subset of the plurality of credibility data with the first component score to detail derivation of the first component score, the second subset of the plurality of credibility data with the second component score to detail derivation of the second component score, and the third subset of the plurality of credibility data with the third component score to detail derivation of the third component score.
9. A computer-implemented method performed by a credibility score system, the computer-implemented method for generating a multi-dimensional credibility score, the computer-implemented method comprising:
with at least one machine of the credibility score system operating via a processor and non-transitory computer-readable memory:
compiling a first set of credibility data comprising sentiment that others have expressed toward a particular entity;
compiling a second set of credibility data comprising information obtained from any detected online presence of the particular entity;
compiling a third set of credibility data comprising trust indicators provided by others that attest to the trustworthiness of the particular entity;
deriving a credibility score from the first, second, and third sets of credibility data; and
presenting the credibility score in response to an inquiry about the particular entity's credibility.
10. The computer-implemented method of claim 9 further comprising producing a sentiment score based on an amount of positivity and negativity expressed in the first set of credibility data.
11. The computer-implemented method of claim 10 further comprising generating a relative sentiment score based on clustering of the particular entity's sentiment score with sentiment scores produced for other entities.
12. The computer-implemented method of claim 10 further comprising producing a transparency score from the second set of credibility data, the transparency score quantifying the particular entity's online presence based on a degree with which credibility data from at least two different online presences of the particular entity matches.
13. The computer-implemented method of claim 12 further comprising producing a trustworthiness score from the third set of credibility data.
14. The computer-implemented method of claim 9 , wherein the first set of credibility data comprises a plurality of reviews and ratings that are directed to the particular entity.
15. The computer-implemented method of claim 14 , wherein the second set of credibility data comprises identifying information about the particular entity as obtained from at least two different online presences of the particular entity.
16. The computer-implemented method of claim 15 , wherein the third set of credibility data comprises a plurality of accreditations received by the particular entity.
17. The computer-implemented method of claim 9 further comprising compiling a fourth set of credibility data comprising stability indicators for the marketplace viability of the particular entity.
18. The computer-implemented method of 17 , wherein deriving the credibility score comprises deriving the credibility score from a combination of the first, second, third, and fourth sets of credibility data.
19. A computer-implemented method for quantifying a plurality of credibility indicators to a credibility score, the computer-implemented method comprising:
with at least one machine operating via a processor and non-transitory computer-readable memory:
aggregating from a plurality of data sources, credibility data that pertains to any of the plurality of credibility indicators;
increasing the credibility score based on a number of the plurality of the credibility indicators for which credibility data is successfully aggregated;
increasing the credibility score when, for a particular data indicator of the plurality of credibility indicators, first credibility data that is aggregated from a first data source matches with second credibility data that is aggregated from a second data source, wherein the plurality of data sources comprises the first and second data sources;
increasing the credibility score when credibility data for a credibility indicator exceeds a threshold defined for that credibility indicator; and
presenting the credibility score in response to an inquiry about the particular entity's credibility.
20. The computer-implemented method of claim 19 further comprising decreasing the credibility score when the first credibility data for the particular data indicator is different than the second credibility data for the same particular data indicator.
21. The computer-implemented method of claim 20 further comprising presenting the first data source as hosting different credibility data for the particular entity than the second data source.
22. The computer-implemented method of claim 19 further comprising updating the credibility as credibility data for any of the credibility indicators is aggregated.
23. The computer-implemented method of claim 19 further comprising defining a first set of the plurality of data indicators as primary data indicators and a second set of the plurality of data indicators as secondary data indicators, wherein the primary data indicators provide greater impact on the credibility score than the secondary data indicators.