Sanitization of septic news sentences through hybrid approach in English.
News articles play an important role in shaping public opinion and influencing decision-making. Sentences of standard news articles are often manipulated to favour a person, group, or political party or reflect a particular sentiment or agenda. It is challenging to define and filter or sanitize such...
| Published in: | Language Resources & Evaluation Vol. 59; no. 3; pp. 1865 - 1898 |
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| Main Authors: | , |
| Format: | Article |
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Springer Nature
Sep2025
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=186909044&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 186909044 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Sep2025 vid: 59 iid: 3 pid: 237 pub: Springer Nature artinfo: ui: 186909044 10.1007/s10579-024-09778-0 ppf: 1865 ppct: 33 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1MB tig: atl: Sanitization of septic news sentences through hybrid approach in English. aug: au: Das, Soma Chatterji, Sanjay affil: https://ror.org/03c3jbs89 CSE, Indian Institute of Information Technology Kalyani, Kalyani, West Bengal, India https://ror.org/02decng19 CSE, Institute of Engineering & Management, 700091, Kolkata, India su: Machine learning Paraphrase Text processing (Computer science) Fake news Information filtering sug: subj: Machine learning Paraphrase Text processing (Computer science) Fake news Information filtering keyword: GPT News Paraphrasing Rule-based approach Sanitization Sentence transformer Sepsis sentence ab: News articles play an important role in shaping public opinion and influencing decision-making. Sentences of standard news articles are often manipulated to favour a person, group, or political party or reflect a particular sentiment or agenda. It is challenging to define and filter or sanitize such news content before presenting it to readers. In our research, we focus on addressing some of the important issues of problematic English news sentences referred to as Septic sentences. With the aid of Machine Learning algorithms, we have successfully identified these sentences and their corresponding Septic phrases. We sanitize these Septic sentences by converting them into Pure sentences. In our paper, we demonstrate the sanitization process using a hybrid system, i.e., a rule-based approach followed by paraphrasing techniques. We evaluate our models using both syntactic and semantic similarity measured. We leverage the GPT - 3.5 and Parrot models in the direct paraphrasing approach. For Indirect paraphrasing, we use Google Translation API to translate the Septic English sentences into Spanish, German, and Tagalog, followed by back translation into English sentences. Additionally, we use the DeepL API to perform the same task through Spanish. Overall, DeepL model gives the highest accuracy throughout the metrics compared to the other Direct and Indirect methods. 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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