DoSLex: automatic generation of all domain semantically rich sentiment lexicon.
For sentiment analysis, lexicons are among the important resources. Existing sentiment lexicons have a generic polarity for each word. In fact, many words have different polarities when they are used in different domain. For the first time, in this work automation of a domain-specific sentiment lexi...
| Publicado en: | Language Resources & Evaluation Vol. 59; no. 2; pp. 1083 - 1111 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Springer Nature
Jun2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=185240048&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 185240048 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Jun2025 vid: 59 iid: 2 pid: 237 pub: Springer Nature artinfo: ui: 185240048 10.1007/s10579-024-09753-9 ppf: 1083 ppct: 28 formats: fmt: – @attributes: type: T – @attributes: type: P size: 2.2MB tig: atl: DoSLex: automatic generation of all domain semantically rich sentiment lexicon. aug: au: Jain, Minni Jindal, Rajni Jain, Amita affil: https://ror.org/01ztcvt22 Delhi Technological University, New Delhi, Delhi, India https://ror.org/01fczmh85 Netaji Subhas University of Technology, New Delhi, Delhi, India su: Low-resource languages Knowledge base Sentiment analysis Hindi language Lexicon sug: subj: Low-resource languages Knowledge base Sentiment analysis Hindi language Lexicon keyword: Indian languages Lexicon-based methods Multi-lingual BERT Word embedding WordNet ab: For sentiment analysis, lexicons are among the important resources. Existing sentiment lexicons have a generic polarity for each word. In fact, many words have different polarities when they are used in different domain. For the first time, in this work automation of a domain-specific sentiment lexicon named "DoSLex" has been proposed. In DoSLex, all the words are represented in a circle where the centre stands for the domain, and the x and y axis for the strength and the orientation of the sentiment, respectively. In the circle, the radius is the contextual similarity between the domain and term calculated using MuRIL embeddings, and the angle is the prior sentiment score taken from various knowledge bases. The proposed approach is language-independent and can be applied to any domain. The extensive experiments were conducted on three low-resource languages: Hindi, Tamil, and Bangla. The experimental studies discuss the performance of the combinations of different word embeddings (FastText, M-Bert and MuRIL) with several sources of prior sentiment knowledge bases on various domains. The performance of DoSLex has also been compared with three sentiment lexicons, and the results demonstrating a significant improvement in sentiment analysis. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2025. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2025 holdings: @attributes: islocal: N |
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