sentiment analysis based on chinese thinking modes
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Sentiment Analysis Based on Chinese Thinking Modes. Yang Liang. Introduction Thinking models Description of Chinese Sentiment Expression Model Implicit Chinese Sentiment Expression Mining Based on LSA Experiment Setting and Evaluation. Outline. - PowerPoint PPT PresentationTRANSCRIPT
Sentiment Analysis Based
on Chinese Thinking Modes
Yang LiangYang Liang
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Introduction
Thinking models
Description of Chinese Sentiment Expression Model
Implicit Chinese Sentiment Expression Mining Based on LSA
Experiment Setting and Evaluation
Outline
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Sentiment analysis ——a popular research topic in NLP in recent years
◆ Blog ,twitter, comment
Sentiment analysis in China
◆ phase level, sentence level(COAE)
◆ Less work in passage level
Our work
◆ relationships between thinking modes and language
◆ Chinese sentiment expression model and LSA
Introduction
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Introduction
Thinking models
Description of Chinese Sentiment Expression Model
Implicit Chinese Sentiment Expression Mining Based on LSA
Experiment Setting and Evaluation
Outline
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Spiral Graphic Mode and Straight Line Mode
Concreteness and Abstractness
Scatter view and Focus view
Thinking models
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Spiral Graphic Mode
◆ reflects in the passage organization
◆ the topic of the passage is discussed after examples
Straight Line Mode
◆ focus on deduction and thinking in a straight line way
◆ tend to state their views directly and frankly
Spiral Graphic Mode and
Straight Line Mode
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Example
◆ (1) Chinese:
“他被眼前的一幕震惊了。”
English:
“He was shocked by what he saw.”
◆ (2) Chinese:
“经过反复的思考，我终于得到了完美的答案 ”。
English:
“I got a perfect answer after deeply thinking.”
Spiral Graphic Mode and
Straight Line Mode
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Spiral Graphic Mode and Straight Line Mode
Concreteness and Abstractness
Scatter view and Focus view
Thinking models
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Concreteness
◆ Chinese uses quantities of specific words, shapes, sounds and description to illustrate abstract things
Abstractness
◆ English tend to implement general vocabularies and their variants to express abstract feelings or opinions, such as “-ion”, “-ance” and “-ness”
Concreteness and Abstractness
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Example
◆ (1) Chinese:
土崩瓦解。
English:
Disintegration
◆ (2) Chinese:
有志者，事竟成 English:
When there is a will , there is a way.
Concreteness and Abstractness
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Spiral Graphic Mode and Straight Line Mode
Concreteness and Abstractness
Scatter view and Focus view
Thinking models
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Scatter View
◆ Chinese tend to emphasize unified whole
◆ Example : more than one verb is used in one Chinese sentence
Focus View
◆ English pay more attention to logical reasoning or deduction
◆ express their feelings or emotions briefly thinking
Scatter View and Focus View
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Example
◆ (1) Chinese:
他拿着课本走进了教室。
English:
He walked into the classroom with a textbook in hands.
◆ (2) Chinese:
他们俩青梅竹马，两小无猜
English:
The boy and the girl were playmates in their childhood.
Scatter View and Focus View
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Introduction
Thinking models
Description of Chinese Sentiment Expression Model
Implicit Chinese Sentiment Expression Mining Based on LSA
Experiment Setting and Evaluation
Outline
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Quantification of “Spiral Graphic Mode”
◆ emotion-determining words mostly locate the end part of Chinese sentences
◆ the closer ai locates the tail, the larger the score(ai) will be
Description of CSE Model
1 |i ii
score A position a count a A score a
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Quantification of “Concreteness”
◆ Chinese sentiment expression, verb also plays an important role，“脸红”“溃败”
◆ the highest priority to adjective, then the higher priority is given to the verb, finally other words are processed
Description of CSE Model
n m l
adj verbi j k
i j k
score a W W W
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Quantification of “Scatter View”
◆ View window to simulate the Scatter View
◆ fixed at 6
Extend Resource
◆ CRF， COAE
Description of CSE Model
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Quantification of Similarities between Thinking Modes
◆ The similarities between Chinese and English
◆ Example:
1)Chinese: “这个酒店什么都好，就是服务让人失望。”
English: “Every aspect about the hotel is ok except the disappointing service.”
2)脸红， blush
Description of CSE Model
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Introduction
Thinking models
Description of Chinese Sentiment Expression Model
Implicit Chinese Sentiment Expression Mining Based on LSA
Experiment Setting and Evaluation
Outline
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The Criterion of Implicit Emotion Sample
◆ Emotion expressed in an indirect way
◆ the implicit emotion articles ,low scores
◆ group of samples are chosen to determine the threshold,(from DUTIR Emotion Ontology )
Implicit Emotion Classification Based on LSA
◆ LSA, relationships between the implicit samples and the seed samples
Implicit Chinese Sentiment Expression Mining Based on
LSA
,j i i jk jkk
score A sim A s score s
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Introduction
Thinking models
Description of Chinese Sentiment Expression Model
Implicit Chinese Sentiment Expression Mining Based on LSA
Experiment Setting and Evaluation
Outline
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Experiments of Chinese Thinking modes in different domains
◆ Corpus , three domains, 4000 hotel reviews, 1608 electronics reviews and 1047 stock reviews
◆ result
Experiment Setting and Evaluation
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Elec
◆ adding each Chinese thinking mode the precision has increased.
◆ elec-pos reviews is not increasing obviously——too much noun
Experiment Setting and Evaluation
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Stock
◆ stock-neg data set is not good
◆ great number of specialized words exist and part of them does not appear in DUTIR emotion ontology
Experiment Setting and Evaluation
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Experiment of Chinese sentiment expression model and LSA
◆ Experiment results on ChnSentiCorp
◆ Statistic data of implicit samples
Experiment Setting and Evaluation
Lexicon Semantic CSE
Pos 1575/1828(86.16%) 1502/1828(82.17%) 1575/1828(86.16%)
Neg 1727/2163(79.84%) 1811/2163(83.73%) 1827/2163(84.47%)
Total 3302/3991(82.74%) 3313/3991(83.01%) 3402/3991(85.24%)
Lexicon CSEPos-Implicit 751/1575(47.68%) 640/1575(40.63%)Neg-Implicit 836/1827(45.76%) 624/1827(34.15%)
Total 1587/3402(46.65%)
1264/3402(37.15%)
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Secondary classification by implementing LSA
◆ Macro-Average-Precision of different methods in ChnSen
Experiment Setting and Evaluation
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Thanks for your attention