SYSTEM AND METHOD FOR MEASURING SENTIMENT OF TEXT IN CONTEXT
A system and method for determining sentiment comprising receiving textual data, identifying a context for the textual data, selecting and/or modifying a natural language processor based on the context, analyzing the textual data with the natural language processor for a sentiment determination, and storing the sentiment determination on a non-transitory computer readable medium.
1 . A computer implemented method for analyzing textual data to determine a context aware sentiment, comprising:
receiving textual data from a social media server;
analyzing the received social media data to identify a context for the received textual data;
selecting a natural language processor based on the identified context of the received textual data;
analyzing the textual data using the natural language processor to determine a sentiment to be associated with the textual data; and
storing the determined sentiment on a non-transitory computer readable medium.
2 . The method of claim 1 wherein identifying a context for the textual data comprises conducting a match between the textual data and a keyword associate with the context.
3 . The method of claim 1 wherein storing the determined sentiment on the non-transitory computer readable medium comprises associating the textual data with the determined sentiment.
4 . The method of claim 3 wherein storing the determined sentiment on the non-transitory computer readable medium comprises associating the textual data and determined sentiment with a context label.
5 . A computer implemented method for analyzing textual data to determine a context aware sentiment, comprising:
receiving textual data from a server;
analyzing the received textual data to determine a sentiment associated with the received textual data and a speech element extracted from the received textual data;
analyzing the received textual data to identify an object associated with the speech element within the received textual data associated with the sentiment;
matching the object to a topic; and
storing the topic and the determined sentiment on a non-transitory computer readable medium.
6 . The method of claim 5 wherein the speech element is a verb or a verb phrase and the object is the object of the verb or verb phrase.
7 . The method of claim 5 wherein matching the object to the topic comprises conducting a regular expression match on a keyword set associated with the topic.
8 . The method of claim 5 further comprising identifying a subject within the textual data associated with the determined sentiment from the speech element.
9 . The method of claim 8 further comprising, matching the subject to a second topic.
10 . The method of claim 9 further comprising, changing the sentiment to a second sentiment which applies to the subject and storing the second sentiment on a non-transitory computer readable medium.
11 . The method of claim 10 wherein storing the second sentiment on the non-transitory computer readable medium comprises annotating the textual data with the subject and second sentiment.
12 . The method of claim 11 wherein the speech element is a verb or verb phrase and the object is the object of the verb phrase and the subject is the subject of the verb.
13 . A computer implemented method for context aware sentiment analysis on textual data comprising:
receiving textual data from a server;
identifying a context for the received textual data;
modifying a natural language processor to identify a sentiment value associated with the received textual data in accordance with the context;
determining the sentiment value and associated parts of speech with the natural language processor;
identifying an object within the textual data associated with the sentiment from the associated parts of speech;
matching the object to a topic; and
storing the topic, object, and sentiment on a non-transitory computer readable medium.
14 . The method of claim 13 wherein the associated parts of speech is a verb or verb phrase and the object is the object of the verb.
15 . The method of claim 13 wherein matching the object to a topic comprises conducting a regular expression match on a keyword set for the topic.
16 . The method of claim 15 further comprising, identifying a subject within the textual data associated with the sentiment from the associated parts of speech.
17 . The method of claim 16 further comprising, changing the sentiment to a second sentiment which applies to the subject and storing the second sentiment on a non-transitory computer readable medium.
18 . The method of claim 17 wherein identifying a context for the textual data comprises conducting a regular expression match between the textual data and a keyword set for the context.
19 . The method of claim 18 wherein storing the topic, object, and sentiment on a non-transitory computer readable medium comprises annotating the textual data with the topic, object and sentiment.
20 . The method of claim 18 further comprising annotating the textual data with the subject.
21 . A system for determining sentiment from textual data comprising:
a non-transitory computer readable medium storing textual data;
a processor executing programming instructions to:
identify a context for the textual data,
select a natural language processor based on the identified context,
analyze the data using the natural language processor to determine a sentiment value, and
store the determined sentiment on the non-transitory computer readable medium.
22 . The system of claim 21 , wherein the processor executes programming instructions to annotate the textual data with the determined sentiment and to store the determined sentiment and annotated textual data on the non-transitory computer readable medium.
23 . The system of claim 22 wherein the processor executes programming instructions to annotate the textual data and determined sentiment with a context label and to store the annotated textual data, determined sentiment and context label on the non-transitory computer readable medium.