In a method for analyzing social media messages, the method includes one or more processors analyzing social media messages utilizing a set of topics and keywords associated with a brand. The method further includes one or more processors identifying social media messages that include information relating to the brand utilizing the analysis of social media messages utilizing the set of topics and keywords. The method further includes one or more processors determining relevancy scores for the identified social media messages that provide an indication of the percentage likelihood that a social media message is related to the brand. The method further includes one or more processors determining one or more recommendations of social media users associated with social media messages based on the determined relevancy scores.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for analyzing social media messages, the method comprising: analyzing, by one or more processors, social media messages utilizing a set of topics and keywords associated with a brand; identifying, by one or more processors, social media messages that include information relating to the brand utilizing the analysis of social media messages utilizing the set of topics and keywords; determining, by one or more processors, relevancy scores for the identified social media messages that provide an indication of a percentage likelihood that a social media message is related to the brand; and determining, by one or more processors, one or more recommendations of social media users associated with social media messages based on the determined relevancy scores. 2. The method of claim 1, further comprising: receiving, by one or more processors, a selection of one or more of the recommendations of social media users; and sending, by one or more processors, a promotional campaign brand message to the received selection of one or more social media users. 3. The method of claim 1, wherein the analyzing social media messages utilizing a set of topics and keywords associated with a brand, further comprises: filtering, by one or more processors, social media messages based on context of the social media messages to identify a filtered set of social media messages; and analyzing, by one or more processors, the filtered set of social media messages utilizing the set of topics and keywords associated with the brand. 4. The method of claim 1, further comprising: determining, by one or more processors, the set of topics and keywords associated with the brand utilizing a matrix factorization topic model. 5. The method of claim 3, wherein text extractors utilize the set of topics and keywords associated with the brand to identify social media messages, from the filtered set of social medial messages, that include information relating to the brand. 6. The method of claim 1, wherein the determining one or more recommendations of social media users associated with social media messages based on the determined relevancy scores, further comprises: determining, by one or more processors, which social media messages have a relevancy score that meets or exceeds a threshold condition; and determining, by one or more processors, one or more recommendations of social media users based on the social media messages that meet or exceed the threshold condition. 7. The method of claim 2, further comprising: storing, by one or more processors, the received selections of one or more of the recommendations of social media users; and creating, by one or more processors, an updated analysis model for identifying social media users that include information relating to the brand and an updated analysis model for determining relevancy scores, based on the stored selections of recommendations. 8. A computer program product for analyzing social media messages, the computer program product comprising: one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the program instructions comprising: program instructions to analyze social media messages utilizing a set of topics and keywords associated with a brand; program instructions to identify social media messages that include information relating to the brand utilizing the analysis of social media messages utilizing the set of topics and keywords; program instructions to determine relevancy scores for the identified social media messages that provide an indication of a percentage likelihood that a social media message is related to the brand; and program instructions to determine one or more recommendations of social media users associated with social media messages based on the determined relevancy scores. 9. The computer program product of claim 8, further comprising program instructions, stored on the one or more computer readable storage media, to: receive a selection of one or more of the recommendations of social media users; and send a promotional campaign brand message to the received selection of one or more social media users. 10. The computer program product of claim 8, wherein the program instructions to analyze social media messages utilizing a set of topics and keywords associated with a brand, further comprise program instructions to: filter social media messages based on context of the social media messages to identify a filtered set of social media messages; and analyze the filtered set of social media messages utilizing the set of topics and keywords associated with the brand. 11. The computer program product of claim 8, further comprising program instructions, stored on the one or more computer readable storage media, to: determine the set of topics and keywords associated with the brand utilizing a matrix factorization topic model. 12. The computer program product of claim 10, wherein text extractors utilize the set of topics and keywords associated with the brand to identify social media messages, from the filtered set of social medial messages, that include information relating to the brand. 13. The computer program product of claim 8, wherein the program instructions to determine one or more recommendations of social media users associated with social media messages based on the determined relevancy scores, further comprise program instructions to: determine which social media messages have a relevancy score that meets or exceeds a threshold condition; and determine one or more recommendations of social media users based on the social media messages that meet or exceed the threshold condition. 14. The computer program product of claim 9, further comprising program instructions, stored on the one or more computer readable storage media, to: store the received selections of one or more of the recommendations of social media users; and create an updated analysis model for identifying social media users that include information relating to the brand and an updated analysis model for determining relevancy scores, based on the stored selections of recommendations. 15. A computer system for analyzing social media messages, the computer system comprising: one or more computer processors; one or more computer readable storage media; and program instructions stored on the computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to analyze social media messages utilizing a set of topics and keywords associated with a brand; program instructions to identify social media messages that include information relating to the brand utilizing the analysis of social media messages utilizing the set of topics and keywords; program instructions to determine relevancy scores for the identified social media messages that provide an indication of a percentage likelihood that a social media message is related to the brand; and program instructions to determine one or more recommendations of social media users associated with social media messages based on the determined relevancy scores. 16. The computer system of claim 15, further comprising program instructions, stored on the computer readable storage media for execution by at least one of the one or more processors, to: receive a selection of one or more of the recommendations of social media users; and send a promotional campaign brand message to the received selection of one or more social media users. 17. The computer system of claim 15, wherein the program instructions to analyze social media messages utilizing a set of topics and keywords associated with a brand, further comprise program instructions to: filter social media messages based on context of the social media messages to identify a filtered set of social media messages; and analyze the filtered set of social media messages utilizing the set of topics and keywords associated with the brand. 18. The computer system of claim 15, further comprising program instructions, stored on the computer readable storage media for execution by at least one of the one or more processors, to: determine the set of topics and keywords associated with the brand utilizing a matrix factorization topic model. 19. The computer system of claim 15, wherein the program instructions to determine one or more recommendations of social media users associated with social media messages based on the determined relevancy scores, further comprise program instructions to: determine which social media messages have a relevancy score that meets or exceeds a threshold condition; and determine one or more recommendations of social media users based on the social media messages that meet or exceed the threshold condition. 20. The computer system of claim 16, further comprising program instructions, stored on the computer readable storage media for execution by at least one of the one or more processors, to: store the received selections of one or more of the recommendations of social media users; and create an updated analysis model for identifying social media users that include information relating to the brand and an updated analysis model for determining relevancy scores, based on the stored selections of recommendations.