TOPIC-SPECIFIC SENTIMENT EXTRACTION
First Claim
1. A method for sentiment extraction, comprising:
- receiving one or more expressions, wherein respective expressions comprise a set of one or more words, wherein one or more of the expressions is associated with a target;
extracting one or more candidate expressions from one or more of the expressions, wherein one or more of the candidate expressions comprises a subset of the set of one or more words;
identifying one or more relationships between one or more pairs of candidate expressions from respective expressions and frequencies of respective relationships across one or more of the expressions; and
determining one or more polarities for one or more of the candidate expressions based on one or more positive polarity probabilities for respective candidate expressions, one or more negative polarity probabilities for respective candidate expressions, one or more consistency probabilities for one or more pairs of candidate expressions, one or more inconsistency probabilities for one or more pairs of candidate expressions, and the frequencies of one or more of the relationships between pairs of candidate expressions across one or more of the expressions,wherein the receiving, the extracting, the identifying, or the determining is implemented via a processing unit.
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Abstract
One or more embodiments of techniques or systems for sentiment extraction are provided herein. From a corpus or group of social media data which includes one or more expressions pertaining to a topic, target topic, or a target, one or more candidate expressions may be extracted. Relationships between one or more pairs of candidate expressions may be identified or evaluated. For example, a consistency relationship or an inconsistency relationship between a pair may be determined. A root word database may include one or more root words which facilitate identification of candidate expressions. Among one or more of the root words may be seed words, which may be associated with a predetermined polarity. To this end, polarities may be determined based on a formulation which assigns polarities to a sentiment expression, candidate expressions, or an expression as a constrained optimization problem.
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Citations
20 Claims
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1. A method for sentiment extraction, comprising:
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receiving one or more expressions, wherein respective expressions comprise a set of one or more words, wherein one or more of the expressions is associated with a target; extracting one or more candidate expressions from one or more of the expressions, wherein one or more of the candidate expressions comprises a subset of the set of one or more words; identifying one or more relationships between one or more pairs of candidate expressions from respective expressions and frequencies of respective relationships across one or more of the expressions; and determining one or more polarities for one or more of the candidate expressions based on one or more positive polarity probabilities for respective candidate expressions, one or more negative polarity probabilities for respective candidate expressions, one or more consistency probabilities for one or more pairs of candidate expressions, one or more inconsistency probabilities for one or more pairs of candidate expressions, and the frequencies of one or more of the relationships between pairs of candidate expressions across one or more of the expressions, wherein the receiving, the extracting, the identifying, or the determining is implemented via a processing unit. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19)
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15. A system for sentiment extraction, comprising:
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a root word database comprising one or more root words, wherein one or more of the root words are seed words; a monitoring component receiving one or more expressions, wherein respective expressions comprise a set of one or more words, wherein one or more of the expressions is associated with a target; a parsing component extracting one or more candidate expressions from one or more of the expressions, wherein one or more of the candidate expressions comprises one or more of the root words; a relationship component identifying one or more consistency relationships or one or more inconsistency relationships between one or more pairs of candidate expressions from respective expressions and frequencies of respective relationships across one or more of the expressions; and an optimization component minimizing an objective function associated with one or more polarities for one or more of the candidate expressions based on one or more positive polarity probabilities for respective candidate expressions, one or more negative polarity probabilities for respective candidate expressions, one or more consistency probabilities for one or more pairs of candidate expressions, one or more inconsistency probabilities for one or more pairs of candidate expressions, and the frequencies of one or more of the relationships between pairs of candidate expressions across one or more of the expressions, wherein the root word database, the monitoring component, the parsing component, the relationship component, or the optimization component is implemented via a processing unit.
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20. A computer-readable storage medium comprising computer-executable instructions, which when executed via a processing unit on a computer performs acts, comprising:
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receiving one or more expressions, wherein respective expressions comprise a set of one or more words, wherein one or more of the expressions is associated with a target; extracting one or more candidate expressions from one or more of the expressions, wherein one or more of the candidate expressions comprises a subset of the set of one or more words; identifying one or more relationships between one or more pairs of candidate expressions from respective expressions and frequencies of respective relationships across one or more of the expressions; and determining one or more polarities for one or more of the candidate expressions based on one or more positive polarity probabilities for respective candidate expressions, one or more negative polarity probabilities for respective candidate expressions, one or more consistency probabilities for one or more pairs of candidate expressions, one or more inconsistency probabilities for one or more pairs of candidate expressions, and the frequencies of one or more of the relationships between pairs of candidate expressions across one or more of the expressions.
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Specification