A blog emotion corpus for emotional expression analysis in Chinese

Quan, Changqin; Ren, Fuji

doi:10.1016/j.csl.2010.02.002

Cited by 106 publications

(58 citation statements)

References 19 publications

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“…Based on the analysis of Chinese emotional keywords, about 40% of emotional keywords are verbs, the rest are composed of nouns, adjectives and so on. So we should not focus on only transitive verbs [11]. Actually, these problems also existed in most current machine coding systems.…”

Section: Related Workmentioning

confidence: 97%

“…We build emotional dictionary based on the previous work of our lab [11]. Through analysis on 500 Chinese blogs from July 2008 to January 2009, more than 10000 Chinese emotional keywords are annotated with eight categories (expect, joy, love, surprise, anxiety, sorrow, angry and hate) of emotional value from 0 to 1 by hand.…”

Section: Emotional Dictionarymentioning

confidence: 99%

“…We will review achievement of previous researchers and discuss limitation of them in next section. Based on previous work of our lab [4,5,11], we proposed our method of extracting emotional attribute of relations between countries based on syntactical analysis. It can discovery emotion among multi-countries from Chinese news event.…”

Section: Introductionmentioning

confidence: 99%

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An improved method of extracting emotional attribute of relations based on syntactical analysis

Wang

Ren

2011

2011 IEEE International Conference on Cloud Computing and Intelligence Systems

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Social network plays an important role in this network age. With development of social network, people hope more attribute and more precise description about relation which is the key element of network. This paper proposes an improved method of extracting emotional attribute of relations from Chinese events based on syntactical analysis. In our work, we improved the defect of previous method that can not deal with multiple entities in one sentence. In addition, a large-scale Chinese emotional dictionary not only emotional verbs was used in the extraction of emotional attribute. Experiment showed our method achieved satisfied performance.

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Section: Related Workmentioning

confidence: 97%

Section: Emotional Dictionarymentioning

confidence: 99%

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An improved method of extracting emotional attribute of relations based on syntactical analysis

Wang

Ren

2011

2011 IEEE International Conference on Cloud Computing and Intelligence Systems

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“…The LiveJournal mood annotation standard offers a rich vocabulary to describe the writer's mood. However, this richness has been considered troublesome to generalize the data in a meaningful manner (Quan and Ren, 2010).…”

Section: Emotion Corporamentioning

confidence: 99%

“…One kind of these services are blogs, open diaries in which people encapsulate their own experiences, opinions and feelings to be read and commented by other people. Recently blogs have come into the focus of opinion mining or sentiment and affect analysis (Aman and Szpakowicz, 2007;Quan and Ren, 2010). Therefore creating a large blog-based emotion corpus could help overcome both problems: the lack in quantity of corpora and their applicability in sentiment and affect analysis.…”

Section: Introductionmentioning

confidence: 99%

Automatically annotating a five-billion-word corpus of Japanese blogs for sentiment and affect analysis

Ptaszyński

Rzepka

Araki

et al. 2014

Computer Speech & Language

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This paper presents our research on automatic annotation of a five-billion-word corpus of Japanese blogs with information on affect and sentiment. We first perform a study in emotion blog corpora to discover that there has been no large scale emotion corpus available for the Japanese language. We choose the largest blog corpus for the language and annotate it with the use of two systems for affect analysis: ML-Ask for word-and sentence-level affect analysis and CAO for detailed analysis of emoticons. The annotated information includes affective features like sentence subjectivity (emotive/non-emotive) or emotion classes (joy, sadness, etc.), useful in affect analysis. The annotations are also generalized on a 2-dimensional model of affect to obtain information on sentence valence/polarity (positive/negative) useful in sentiment analysis. The annotations are evaluated in several ways. Firstly, on a test set of a thousand sentences extracted randomly and evaluated by over forty respondents. Secondly, the statistics of annotations are compared to other existing emotion blog corpora. Finally, the corpus is applied in several tasks, such as generation of emotion object ontology or retrieval of emotional and moral consequences of actions.

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A novel fast fractal image coding algorithm based on texture feature

Wang

Ren

Suzuki

2012

IEEJ Transactions Elec Engng

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A novel, fast fractal image coding algorithm based on the texture feature is proposed in this paper. Fractal image coding is a very promising technique for image compression. However, it has not been widely used because of the long encoding time and high computational complexity. The most fractal image encoding time is spent in determining the approximate D-block from a large D-blocks library by using the global searching method. Clustering the D-blocks library is an effective method to reduce the encoding time. First, all the D-blocks are clustered into several parts based on the new texture feature α derived from variation function; second, for each R-block, the approximate D-blocks are searched for in the same part. In the search process, we import control parameter δ; this step avoids losing the most approximate D-block for each R-block. Finally, the R-blocks whose least errors are larger than the threshold given in advance are coded by the quad tree method. We have performed a simulation with MATLABR2010a to verify the effectiveness of the proposed algorithm. The experimental results show that the proposed algorithm can be over 6 times faster than the moment-feature-based fractal image algorithm; in addition, the proposed algorithm also improves the quality of the decoded image and increases the PSNR's average value by 2 dB. The comparisons demonstrate that this method is better than the fractal image coding algorithm based on statistical features.

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A blog emotion corpus for emotional expression analysis in Chinese

Cited by 106 publications

References 19 publications

An improved method of extracting emotional attribute of relations based on syntactical analysis

An improved method of extracting emotional attribute of relations based on syntactical analysis

Automatically annotating a five-billion-word corpus of Japanese blogs for sentiment and affect analysis

A novel fast fractal image coding algorithm based on texture feature

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