Systems and methods for categorizing and moderating user-generated content in an online environment

1. An apparatus, comprising:

a storage device that stores a set of instructions; and

at least one processor coupled to the storage device, the at least one processor being operative with the set of instructions in order to:

receive, over an electronic network, at least a portion of textual data from a user interface on a display device;

compute a numeric likelihood that the received portion of textual data falls into a first selected category unsuitable for publication on a web page in an online environment;

determine whether to electronically publish the received portion of textual data on the web page on the display device online environment based on a comparison of the computed numeric likelihood to a set of threshold values associated with the first selected category, wherein:

the set comprises (i) a first threshold value representative of numeric likelihoods assigned to a first portion of reference content suitable for publication on the web page in the online environment, and (ii) a second threshold value representative of numeric likelihoods assigned to a second portion of the reference content unsuitable for publication on the web page in the online environment; and

the second threshold value exceeds the first threshold value;

determine whether the computed numeric likelihood exceeds the first threshold value; and

generate an electronic command to publish the textual data on the web page in the online environment, when the computed numeric likelihood is determined not to exceed the first threshold value.

2. The apparatus of claim 1 , wherein the at least one processor is further operative with the set of instructions to assign, to the user, a value indicative of a capability of the user to generate content suitable for publication on the web page in the online environment.

3. The apparatus of claim 1 , wherein the at least one processor is further operative with the set of instructions to establish that the textual data is unsuitable for publication on the web page in the online environment, when the computed numeric likelihood is determined to exceed the first threshold value.

4. The apparatus of claim 1 , wherein the at least one processor is further operative with the set of instructions to, when the computed numeric likelihood is determined to exceed the first threshold value, determine whether the computed numeric likelihood exceeds the second threshold value.

5. The apparatus of claim 4 , wherein the at least one processor is further operative with the set of instructions to establish that the textual data is unsuitable for publication on the web page in the online environment, when the computed numeric likelihood is determined to exceed the first and second threshold values.

6. The apparatus of claim 4 , wherein the at least one processor is further operative with the set of instructions to:

identify a user as having a predetermined expertise level, when the computed numeric likelihood is determined to exceed the first threshold value and to not exceed the second threshold value, the predetermined expertise level being indicative of a capability of the user to generate content suitable for publication on the web page in the online environment;

generate an electronic command to transmit information associated with the textual data to the display device associated with the user, the information instructing the display device to present at least a portion of the textual data to the user;

receive a response to the transmitted information from the display device, the response being indicative a determination, by the user, of a suitability of the textual data for publication on the web page in the online environment; and

determine whether to electronically publish the textual data on the web page in the online environment based on the received response.

7. The apparatus of claim 1 , wherein the at least one processor is further operative with the set of instructions to:

parse the textual data into a plurality of n-grams; and

compute the numeric likelihood based on an application of a machine-learning algorithm to the plurality of n-grams.

8. The apparatus of claim 1 , wherein:

the textual data comprises a comment generated by a user for publication on a web page; and

the second portion of the reference content comprises at least one of an abusive comment or spam.

9. A computer-implemented method, comprising:

receiving, over an electronic network, at least a portion of textual data from a user interface on a display device;

computing, using at least one processor, a numeric likelihood that the received portion of textual data falls into a first selected category unsuitable for publication on a web page in an online environment;

determining, using the at least one processor, whether to electronically publish the received portion of textual data on the web page on the display device online environment based on a comparison of the computed numeric likelihood to a set of threshold values associated with the first selected category, wherein:

the set comprises (i) a first threshold value representative of numeric likelihoods assigned to a first portion of reference content suitable for publication on the web page in the online environment, and (ii) a second threshold value representative of numeric likelihoods assigned to a second portion of the reference content unsuitable for publication on the web page in the online environment; and

the second threshold value exceeds the first threshold value;

determining, using the at least one processor, whether the computed numeric likelihood exceeds the first threshold value; and

generating, using the at least one processor, an electronic command to publish the textual data on the web page in the online environment, when the computed numeric likelihood is determined not to exceed the first threshold value.

10. The method of claim 9 , further comprising:

receiving at least a portion of the textual data from the display device of a user, the textual data portion being generated by the user; and

assigning, to the user, a value indicative of a capability of the user to generate content suitable for publication on the web page in the online environment.

11. The method of claim 9 , further comprising establishing that the textual data is unsuitable for publication on the web page in the online environment, when the computed numeric likelihood is determined to exceed the first threshold value.

12. The method of claim 9 , further comprising, when the computed numeric likelihood is determined to exceed the first threshold value, determining whether the computed numeric likelihood exceeds the second threshold value.

13. The method of claim 12 , further comprising establishing that the textual data is unsuitable for publication on the web page in the online environment, when the computed numeric likelihood is determined to exceed the first and second threshold values.

14. The method of claim 12 , further comprising:

identifying a user as having a predetermined expertise level, when the computed numeric likelihood is determined to exceed the first threshold value and to not exceed the second threshold value, the predetermined expertise level being indicative of a capability of the user to generate content suitable for publication on the web page in the online environment;

generating an electronic command to transmit information associated with the textual data to the display device associated with the user, the information instructing the display device to present at least a portion of the textual data to the user;

receiving a response to the transmitted information from the display device, the response being indicative a determination, by the user, of a suitability of the textual data for publication on the web page in the online environment; and

determining whether to electronically publish the textual data on the web page in the online environment based on the received response.

15. The method of claim 9 , further comprising:

parsing the textual data into a plurality of n-grams; and

computing the numeric likelihood based on an application of a machine-learning algorithm to the plurality of n-grams.

16. The method of claim 9 , wherein:

the textual data comprises a comment generated by a user for publication on a web page; and

the second portion of the reference content comprises at least one of an abusive comment or spam.

17. A tangible, non-transitory computer-readable medium that stores a set of instructions that, when executed by at least one processor, cause the at least one processor to perform operations comprising:

receiving, over an electronic network, at least a portion of textual data from a user interface on a display device;

computing a numeric likelihood that the received portion of textual data falls into a first selected category unsuitable for publication on a web page in an online environment; and

determining whether to electronically publish the received portion of textual data on the web page on the display device online environment based on a comparison of the computed numeric likelihood to a set of threshold values associated with the first selected category, wherein:

the set comprises (i) a first threshold value representative of numeric likelihoods assigned to a first portion of reference content suitable for publication on the web page in the online environment, and (ii) a second threshold value representative of numeric likelihoods assigned to a second portion of the reference content unsuitable for publication on the web page in the online environment; and

the second threshold value exceeds the first threshold value;

determining, using the at least one processor, whether the computed numeric likelihood exceeds the first threshold value; and

generating, using the at least one processor, an electronic command to publish the textual data on the web page in the online environment, when the computed numeric likelihood is determined not to exceed the first threshold value.