Methods and systems for trending issue identification in text streams

Abstract

This application relates to a systems and methods for trending issue identification in text streams. In one embodiment, a method for improving resolution of a trending issue identified in a set of text streams includes presenting a user interface of an application that is being executed by a computing device. The method also includes receiving a notification including the trending issue that has been identified in the set of text streams based at least in part on textual analysis performed on the set of text streams, and presenting the trending issue on the user interface of the application to enable an action to be performed to resolve the trending issue.

1 . A method for resolving trending issues that are identified through text streams, the method comprising, at a client device:
 interfacing with a server device that identifies a trending issue presented in a plurality of text streams, wherein the trending issue corresponds to at least one computerized operation that is functioning improperly;   receiving, from the server device, at least one solution for resolving the trending issue, wherein the at least one solution comprises instructions that, when executed, resolve the trending issue at least in part;   causing information derived from the trending issue and/or at least one solution to be displayed on a display device that is communicatively coupled to the client device; and   in response to receiving a selection to enact the at least one solution:
 enacting the at least one solution by causing the instructions to be executed. 
   
     
     
         2 . The method of  claim 1 , wherein the information is displayed within a user interface that is generated by the client device and output to the display device. 
     
     
         3 . The method of  claim 1 , wherein the information comprises:
 information about the trending issue,   information about the at least one solution,   information about anomalous keywords detected in the plurality of text streams,   information about an overall volume of the plurality of text streams received over a particular period of time, or   some combination thereof.   
     
     
         4 . The method of  claim 1 , wherein enacting the at least one solution comprises:
 restarting one or more devices associated with the trending issue,   escalating the trending issue to at least one appropriate handler,   providing a mass response to a plurality of users who generated the plurality of text streams,   providing a direct response to at least one user of the plurality of users, or some combination thereof.   
     
     
         5 . The method of  claim 1 , wherein the server device identifies the trending issue by:
 filtering the plurality of text streams using one or more machine learning models trained to identify one or more textual patterns in the plurality of text streams.   
     
     
         6 . The method of  claim 1 , wherein the server device identifies the trending issue by:
 preprocessing the plurality of text streams by tokenizing a portion of the plurality of text streams, removing one or more words from the plurality of text streams, or some combination thereof.   
     
     
         7 . The method of  claim 1 , wherein each of the plurality of text streams are included in a respective electronic message, a respective transcription, a respective chat history, a respective social media post, or a respective review. 
     
     
         8 . A non-transitory computer readable storage medium configured to store first instructions that, when executed by a processor included in a client device, cause the client device to resolve trending issues that are identified through text streams, by carrying out steps that include:
 interfacing with a server device that identifies a trending issue presented in a plurality of text streams, wherein the trending issue corresponds to at least one computerized operation that is functioning improperly;   receiving, from the server device, at least one solution for resolving the trending issue, wherein the at least one solution comprises second instructions that, when executed, resolve the trending issue at least in part;   causing information derived from the trending issue and/or at least one solution to be displayed on a display device that is communicatively coupled to the client device; and   in response to receiving a selection to enact the at least one solution:
 enacting the at least one solution by causing the second instructions to be executed. 
   
     
     
         9 . The non-transitory computer readable storage medium of  claim 8 , wherein the information is displayed within a user interface that is generated by the client device and output to the display device. 
     
     
         10 . The non-transitory computer readable storage medium of  claim 8 , wherein the information comprises:
 information about the trending issue,   information about the at least one solution,   information about anomalous keywords detected in the plurality of text streams,   information about an overall volume of the plurality of text streams received over a particular period of time, or   some combination thereof.   
     
     
         11 . The non-transitory computer readable storage medium of  claim 8 , wherein enacting the at least one solution comprises:
 restarting one or more devices associated with the trending issue,   escalating the trending issue to at least one appropriate handler,   providing a mass response to a plurality of users who generated the plurality of text streams,   providing a direct response to at least one user of the plurality of users, or some combination thereof.   
     
     
         12 . The non-transitory computer readable storage medium of  claim 8 , wherein the server device identifies the trending issue by:
 filtering the plurality of text streams using one or more machine learning models trained to identify one or more textual patterns in the plurality of text streams.   
     
     
         13 . The non-transitory computer readable storage medium of  claim 8 , wherein the server device identifies the trending issue by:
 preprocessing the plurality of text streams by tokenizing a portion of the plurality of text streams, removing one or more words from the plurality of text streams, or some combination thereof.   
     
     
         14 . The non-transitory computer readable storage medium of  claim 8 , wherein each of the plurality of text streams are included in a respective electronic message, a respective transcription, a respective chat history, a respective social media post, or a respective review. 
     
     
         15 . A client device configured to resolve trending issues that are identified through text streams, the client device comprising a processor configured to cause the client device to carry out steps that include:
 interfacing with a server device that identifies a trending issue presented in a plurality of text streams, wherein the trending issue corresponds to at least one computerized operation that is functioning improperly;   receiving, from the server device, at least one solution for resolving the trending issue, wherein the at least one solution comprises instructions that, when executed, resolve the trending issue at least in part;   causing information derived from the trending issue and/or at least one solution to be displayed on a display device that is communicatively coupled to the client device; and   in response to receiving a selection to enact the at least one solution:
 enacting the at least one solution by causing the instructions to be executed. 
   
     
     
         16 . The client device of  claim 15 , wherein the information is displayed within a user interface that is generated by the client device and output to the display device. 
     
     
         17 . The client device of  claim 15 , wherein the information comprises:
 information about the trending issue,   information about the at least one solution,   information about anomalous keywords detected in the plurality of text streams,   information about an overall volume of the plurality of text streams received over a particular period of time, or   some combination thereof.   
     
     
         18 . The client device of  claim 15 , wherein enacting the at least one solution comprises:
 restarting one or more devices associated with the trending issue,   escalating the trending issue to at least one appropriate handler,   providing a mass response to a plurality of users who generated the plurality of text streams,   providing a direct response to at least one user of the plurality of users, or some combination thereof.   
     
     
         19 . The client device of  claim 15 , wherein the server device identifies the trending issue by:
 filtering the plurality of text streams using one or more machine learning models trained to identify one or more textual patterns in the plurality of text streams.   
     
     
         20 . The client device of  claim 15 , wherein the server device identifies the trending issue by:
 preprocessing the plurality of text streams by tokenizing a portion of the plurality of text streams, removing one or more words from the plurality of text streams, or some combination thereof.