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Leng, Dongtian
- Sentiment Classification based on Linguistic Patterns in Citation Context
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PDF Views:83
Authors
Affiliations
1 College of Information and Computer Engineering, Northeast Forestry University, Harbin 150040, CN
1 College of Information and Computer Engineering, Northeast Forestry University, Harbin 150040, CN
Source
Current Science, Vol 117, No 4 (2019), Pagination: 606-616Abstract
When citations occur, authors tend to express their emotions implicitly, which makes it difficult to identify the sentiment of citation context. However, authors will still use specific linguistic patterns to express their emotions in citation context. This article explores the linguistic patterns of emotional expression in citation context, and on this basis recognizes the sentimental polarity of citation context. Conditional random fields (CRF) model is introduced to annotate the logical relationship between syntactic structure and vocabularies in linguistic patterns. By analysing the effect of the generated CRF templates in classifying the subjective/ objective sentences and the positive/negative emotional polarity in citation context, the role of linguistic patterns in classifying the citation sentiment is discussed. Experimental results show that the CRF model based on linguistic patterns is superior to the commonly used support vector machine (SVM) model in both subjective/objective and emotional polarity classification tasks. In the SVM model, the contextual information of citation context is considered by introducing one deep learning model of Word2vec. It shows that extracting linguistic patterns from the citation context helps reflect the way in which an author organizes his/her language in expressing his/her emotions. Extracting these linguistic patterns helps improve the performance of sentiment classification of citation context.Keywords
Citation Context, Conditional Random Fields, Linguistic Patterns, Sentiment Classification, Support Vector Machine.Full Text
References
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Abstract Views :243 |
PDF Views:84
Authors
Affiliations
1 College of Information and Computer Engineering, Northeast Forestry University, Harbin 150040, CN
2 College of Economics and Business Administration, Heilongjiang Institute of Technology, Harbin 150050, CN
1 College of Information and Computer Engineering, Northeast Forestry University, Harbin 150040, CN
2 College of Economics and Business Administration, Heilongjiang Institute of Technology, Harbin 150050, CN
Source
Current Science, Vol 116, No 10 (2019), Pagination: 1696-1705Abstract
This study describes a Laplace transfer-based citation model proposed for the actual citation process among journals. The actual citation process is a dynamic physical system which includes two continuous processes of ageing and publishing of cited articles. By deducing the Laplace transfer function for these two processes, we have established the input–output function for the actual citation process. Considering the subject of ‘automation and control systems’ as an example, time parameters associated with the ageing process were identified from the input–output function to examine the obsolescence characteristics for the subject. Experimental results show that the ageing time parameter calculated by the Laplace transferbased citation model is a good expression on the obsolescence of the field. The field shows a moderate ageing rate and a shortened obsolescence tendency on the whole. Most of the articles cited annually in this field are articles published 5–10 years ago. There is a monotonic decreasing dependence between the increment of IF and the increment of time parameter T1, although IF always increases regardless of whether the ageing tends to prolong or shorten.Keywords
Citation Process, Dynamic Physical System, Impact Factor, Journal Articles, Obsolescence.Full Text
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