Processing and visualization of textual data based on syntactic dependency trees and sentiment scoring

Abstract

Described herein are improved systems and methods for overcoming technical problems associated with processing and visualization of textual data and natural language processing. In some examples, a method is provided for determining sentiment associated with big data analysis of database information. In some examples, textual news data (e.g., NEWS API, RSS, etc.) is received via a communications network from a plurality of data platforms. The textual news data is parsed, and syntactic dependency trees are generated therefrom. A sentiment score is derived for the parsed textual data corresponding to a word or phrase associated with the textual data, and an image is generated reflecting scored sentiment for the parsed textual data.

What is claimed is: 
     
         1 . A method, comprising:
 generating, by a computing system, a dependency tree according to textual news data or a derivative of the textual news data;   determining, by the computing system, a score corresponding to a word or phrase associated with or in the textual news data according to the dependency tree; and   generating, by the computing system, a user interface output comprising the score or a derivative of the score.   
     
     
         2 . The method of  claim 1 , wherein the dependency tree comprises a syntactic dependency tree. 
     
     
         3 . The method of  claim 1 , wherein the score is a sentiment score. 
     
     
         4 . The method of  claim 3 , further comprising displaying, via a graphical user interface (GUI), the sentiment score. 
     
     
         5 . The method of  claim 1 , wherein the user interface output comprises an image. 
     
     
         6 . The method of  claim 1 , further comprising statistical sampling, by the computing system, the textual news data, and wherein the determination of the score is further based on the statistical sampling of the textual news data. 
     
     
         7 . The method of  claim 1 , further comprising prior to determining the score, resolving, by the computing system, ambiguity in the dependency tree, thereby generating a resolved dependency tree, wherein the determination of the score is based on the resolved dependency tree. 
     
     
         8 . The method of  claim 1 ,
 wherein the method is part of an application framework,   wherein the application framework provides searchable content to be searched via a user interface, and   wherein the method further comprises deriving searchable content from the textual news data.   
     
     
         9 . The method of  claim 8 , further comprising providing, via the user interface, search functions using the dependency tree, the score, or a combination thereof as a basis for queries. 
     
     
         10 . The method of  claim 9 , wherein the search functions comprise queries that are definable by a user identifier, a date, positive sentiment, negative sentiment, news attribution, or any combination thereof. 
     
     
         11 . The method of  claim 1 , wherein the textual news data and the derivative of the textual news data comprise application programming interfaces, really simple syndication (RSS) feeds, social media platforms, news aggregators, social news aggregators, or any combination thereof. 
     
     
         12 . The method of  claim 1 , further comprising identifying, by the computing system, sentiment of or related to at least a part of the textual news data based on a source of the textual news data. 
     
     
         13 . The method of  claim 1 , further comprising identifying, by the computing system, sentiment of or related to at least a part of the textual news data based on a date of publication of the textual news data. 
     
     
         14 . A method, comprising:
 constructing, by a computing system, a message comprising textual news data;   generating, by the computing system, a dependency tree according to the message;   determining, by the computing system, a score corresponding to a word or phrase associated with or in the message according to the dependency tree; and   generating, by the computing system, a user interface output comprising the score or a derivative of the score.   
     
     
         15 . The method of  claim 14 , wherein the dependency tree comprises a syntactic dependency tree. 
     
     
         16 . The method of  claim 14 , wherein the score is a sentiment score. 
     
     
         17 . The method of  claim 16 , further comprising displaying, via a graphical user interface (GUI), the sentiment score. 
     
     
         18 . The method of  claim 14 , wherein the user interface output comprises an image. 
     
     
         19 . A non-transitory computer-readable storage medium tangibly encoded with computer-executable instructions, that, when executed by a processor of a computing device the processor performs a method comprising the following operations:
 constructing, by a computing system, a message comprising textual news data;   generating, by the computing system, a dependency tree according to the message;   determining, by the computing system, a score corresponding to a word or phrase associated with or in the message according to the dependency tree; and   generating, by the computing system, a user interface output comprising the score or a derivative of the score.   
     
     
         20 . The non-transitory computer-readable storage medium of  claim 19 , wherein the user interface output comprises an image, and wherein the method further comprises displaying, via a graphical user interface (GUI), the score.