Methods and systems for monitoring and analyzing social media data

Patent metadata

Field	Value
Publication number	US-9256663-B2
Application number	US-201313973927-A
Country	US
Kind code	B2
Filing date	Aug 22, 2013
Priority date	Aug 22, 2013
Publication date	Feb 9, 2016
Grant date	Feb 9, 2016

Abstract

A system and method for analyzing social media data by obtaining social media data from a social media platform, where the social media data includes documents from multiple users of the social media platform; classifying the documents using a sentiment classifier; tokenizing the documents into terms; associating a sentiment with each term; detecting a first event based on a number of occurrences of a first term in the documents; and providing information associated with the event to a user, where the information includes the first term and a sentiment associated with the first term.

First claim

What is claimed is:

1. A method for analyzing social media data, the method comprising:
obtaining, using one or more processors, social media data from a social media platform, wherein the social media data comprises documents from a plurality of users of the social media platform;
classifying the documents using a sentiment classifier;
tokenizing the documents into terms;
associating a sentiment classification with each term;
detecting a first event based on a number of occurrences of a first term in the documents;
providing information associated with the first event to a user, wherein the information comprises the first term and a sentiment classification associated with the first term; and
calculating a term frequency-inverse document frequency (“TFIDF”) metric for the first term, wherein:
the information associated with the first event further comprises the TFIDF metric,
the TFIDF metric is a time normalized TFIDF metric, and
the TFIDF metric is calculated using the formula:

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wherein each “document” is a document that included the first term, “tf” is the term frequency, “idf” is the inverse document frequency, and decay is calculated using a timestamp associated with each document.

2. The method of claim 1 , wherein “decay” is calculated using the formula:
decay= e −(current time-document time)
wherein “document time” is determined based on the timestamp associated with each document.

3. The method of claim 1 , wherein the social media data is obtained in batch format.

4. The method of claim 1 , wherein the social media data is obtained in streaming format.

5. The method of claim 1 , wherein detecting the first event is further based on the sentiment classification associated with the first term.

6. The method of claim 5 , wherein the first event is only detected when the first term is associated with a negative sentiment classification.

7. The method of claim 1 , wherein the information is only provided to the user when the first term is associated with a negative sentiment classification.

8. A system for analyzing social media data, the system comprising:
a processing system comprising one or more processors; and
a memory system comprising one or more computer-readable media, wherein the one or more computer-readable media contain instructions that, when executed by the processing system, cause the processing system to perform operations comprising:
obtaining, using one or more processors, social media data from a social media platform, wherein the social media data comprises documents from a plurality of users of the social media platform;
classifying the documents using a sentiment classifier;
tokenizing the documents into terms;
associating a sentiment classification with each term;
detecting a first event based on a number of occurrences of a first term in the documents; and
providing information associated with the first event to a user, wherein the information comprises the first term and a sentiment classification associated with the first term;
calculating a term frequency-inverse document frequency (“TFIDF”) metric for the first term, wherein:
the information associated with the first event further comprises the TFIDF metric,
the TFIDF metric is a time normalized TFIDF metric and
the TFIDF metric is calculated using the formula:

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F
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document
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documents

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documents

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tf
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term
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document

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decay

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idf
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Assignees

• Xerox Corp

Inventors

• Bhatia Sumit
• Li Jingxuan
• Peng Wei
• Sun Tong

Classifications

• G06F16/285 Primary

  Clustering or classification · CPC title

• G06F17/30598 Primary

  Physics · mapped topic