METHOD AND SYSTEM FOR GENERATING SOCIAL SIGNAL VOCABULARIES

• US 20180293607A1
• Filed: 03/29/2018
• Published: 10/11/2018
• Est. Priority Date: 08/31/2012
• Status: Active Grant

• Current Assignee: TPG Specialty Lending Incorporated
• Original Assignee: Sprinklr Inc.
• Inventors: Huddleston, Erik Lee, Huddleston, Brian, Potter, Tim
• Granted Patent: US 10,489,817 B2
• Time in Patent Office: Days
• CPC Class Codes: G06Q 30/0242 Determining effectiveness of advertisements
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04B 7/26 at least one of which is mobile
• CPC Class Codes: H04L 51/216 Handling conversation history, e.g. grouping of messages in sessions or threads
• CPC Class Codes: H04L 51/52 for supporting social networking services
• CPC Class Codes: H04L 65/403 Arrangements for multi-party communication, e.g. for conferences data switching systems for conference H04L12/18; arrangements for connecting several subscribers to a common circuit, i.e. affording conference facilities H04M3/56; television conferencing systems H04N7/15

Abstract

A social analytic system may identify the social signals associated with a brand, campaign, or any other topic. The social analytic system may generate a vocabulary associated with the brand, campaign, or topic based terms used in the associated social signals. The vocabulary may be used for generating social media analytics and identifying social media events, such as marketing campaigns. In one example, a vocabulary may be compared with vocabularies associated with different constituents to identify the positive and negative terms in the vocabulary.

Claims

1-10. -10. (canceled)

11. An apparatus, comprising:

a memory configured to store social signal data based on social signals published using social media accounts, the social signal data including first information that includes a content of the social signals and second information that is different than the first information, wherein the second information includes metadata; and

a processor to generate additional social signal data using the social signal data, the processor configured to;

identify conversations in the social signals using said second information;

group the conversations into clusters using the first information and based on similarity of terms of social signals of the conversations, including;

form a first set of clusters that corresponds to a first time; and

form one or more second sets of clusters that correspond to one or more second different times, respectively; and

wherein, responsive to the grouping using the first information, a first one of the conversations is grouped with a second one of the conversations into a same one of the clusters of the first set or the one or more second sets, the first one of the conversations based on a root social signal of the social signals that is not explicitly linked, by the second information, with a different root social signal on which the second one of the conversations is based, and wherein the additional social signal data includes information about the clusters; and

the processor is further configured to output display data derived from the additional social signal data.

12. The apparatus of claim 11, wherein link the clusters together into the plurality of conversation streams comprises:

generate probabilities for terms associated with the clusters;

generate similarity values between the clusters based on the probabilities for the terms that match in different ones of the clusters; and

link the clusters together into the plurality of conversation streams based on the similarity values.

13. The apparatus of claim 11, wherein output the display data further comprises provide the display data to a web browser or mobile device application.

14. The apparatus of claim 13, wherein the display data comprises an electronic web page.

15. The apparatus of claim 11, wherein generate the additional social signal data using the social signal data further comprises:

link the clusters together into a plurality of conversation streams, wherein a first conversation stream of the plurality of conversation streams includes a cluster of the first set and at least one associated cluster of the one or more second sets, and wherein a second conversation stream of the plurality of conversation streams includes a different cluster of the first set and at least one associated cluster of the one or more second sets.

16. The apparatus of claim 15, wherein generate the additional social signal data using the social signal data further comprises:

calculate strengths of the different conversation streams based on a quantity of the social signals contributing to the conversation streams and a quantity and types of followers associated with the conversation streams; and

derive a score for one of the social media accounts based on the strengths of the conversation streams.

17. The apparatus of claim 11, wherein output the display data derived from the additional social signal data further comprises cause a continuous time series image flows representing the conversation streams to be displayed, and wherein the processor is further configured to:

identify overall sentiments for topics associated with the conversation streams; and

cause indicators to be displayed in conjunction with the time series image flows to indicate changes in the overall sentiments for the topics associated with the conversation streams.

18. The apparatus of claim 17, wherein the processor is further configured to:

identify a quantity of the social signals associated with each of the conversation streams; and

cause different widths of the continuous time series image flows to be displayed based on the quantity of the social signals associated with each of the conversation streams.

19. The apparatus of claim 17, wherein the processor is further configured to:

generate social metrics for the conversation streams; and

cause the social metrics to be displayed in response to detecting selection of the images representing the conversation streams.

20. The apparatus of claim 11, wherein the processor is further configured to:

generate a context distribution from the social signals;

generate candidate labels from the context distribution;

generate joint distributions for the candidate labels;

generate topic distributions for the clusters;

derive mutual information values for the candidate labels based on the joint distributions for the candidate labels and the topic distributions for the clusters; and

select the candidate labels as labels for the clusters based on the mutual information values.

21. The apparatus of claim 11, wherein identifying the conversations in the social signals using the second information comprises identifying ones of the socials signals associated with a same root message.

22. The apparatus of claim 11, wherein the metadata is included in the social signals.

23. The apparatus of claim 11, wherein the first time corresponds to a first day and the second time corresponds to a second different day.

24. The apparatus of claim 11, wherein the processor is further configured to:

identify topic distributions for the clusters by identifying probabilities for terms in the clusters;

generate a context distribution from the social signals;

identify candidate labels from the context distribution;

generate joint distributions for the candidate labels by identifying different groups of the social signals that include terms from the candidate labels and identifying probabilities for terms in the identified groups of social signals;

derive mutual information values for the candidate labels by applying the joint distributions for the candidate labels to the topic distributions for the clusters; and

select topic labels for the clusters from the candidate labels with the largest mutual information values.

25. The apparatus of claim 24, wherein the processor is further configured to link the clusters for different days together as conversation streams based on the topic labels, wherein a first conversation steam of the plurality of conversation streams includes a cluster of the first set and at least one associated cluster of the one or more second sets, and wherein a second conversation stream of the plurality of conversation streams includes a different cluster of the first set and at least one associated cluster of the one or more second sets.