sentiment analysis based on chinese thinking modes

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