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dc.contributor.authorPavan, Luca
dc.date.accessioned2023-09-18T16:19:35Z
dc.date.available2023-09-18T16:19:35Z
dc.date.issued2022
dc.identifier.issn2708-0099
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/113210
dc.description.abstractThis paper describes a dictionary-based software for topic analysis written by the author. The dictionary was created manually. Many studies showed the advantages of using dictionaries to analyze texts. The software described here works in English and Italian languages, and it does not make use of probabilistic methods. In natural language processing, the use of a lexicon to reveal topics in a text is often avoided. Topics depend very much on the context. Assigning unique words to each topic does not help to check the topics in different contexts. However, the software, with a dictionary of about 5,500 topic words described in the paper, in many cases, allows the same word to fall into different topics. This approach allows one to find the main topics in a text, which corresponds to the most frequent topic words detected by the software. Advantages and disadvantages are discussed in the paper, along with examples. The software was extensively tested on large texts, such as Internet news corpora and classics of English and American literature, showing very high reliability in detecting the main topics. Analysis of topics in literaryworks demonstrates almost the same conclusions as were reached by critics.eng
dc.formatPDF
dc.format.extentp. 48-52
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyJ-Gate
dc.relation.isreferencedbyScilit
dc.relation.isreferencedbyDimensions
dc.relation.isreferencedbyLinguistic Bibliography
dc.relation.isreferencedbyMLA: International Bibliography
dc.rightsLaisvai prieinamas internete
dc.source.urihttps://al-kindipublisher.com/index.php/ijllt/article/view/4389/3772
dc.source.urihttps://talpykla.elaba.lt/elaba-fedora/objects/elaba:148057680/datastreams/MAIN/content
dc.titleDetecting main topics using dictionary-based topic analysis
dc.typeStraipsnis kitoje DB / Article in other DB
dcterms.accessRightsThis article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) 4.0 license (https://creativecommons.org/licenses/by/4.0/). Published by Al-Kindi Centre for Research and Development, London, United Kingdom.
dcterms.licenseCreative Commons – Attribution – 4.0 International
dcterms.references12
dc.type.pubtypeS3 - Straipsnis kitoje DB / Article in other DB
dc.contributor.institutionVilniaus universitetas Vilniaus Gedimino technikos universitetas
dc.contributor.facultyKūrybinių industrijų fakultetas / Faculty of Creative Industries
dc.contributor.departmentProfesinės kalbos studijų centras / Professional Language Studies Centre
dc.subject.researchfieldH 004 - Filologija / Philology
dc.subject.studydirectionN07 - Kalbos studijos / Language studies
dc.subject.vgtuprioritizedfieldsEV04 - Komunikacijos valdymas įtraukioje ir kūrybingoje visuomenėje / Communication management in inclusive and creative society
dc.subject.ltspecializationsL103 - Įtrauki ir kūrybinga visuomenė / Inclusive and creative society
dc.subject.encomputational linguistics
dc.subject.entopic analysis
dc.subject.enEnglish literature
dc.subject.enAmerican literature
dc.subject.enItalian literature
dcterms.sourcetitleInternational journal of linguistics, literature and translation
dc.description.issueiss. 12
dc.description.volumevol. 5
dc.publisher.nameAl-Kindi Center for Research and Development
dc.publisher.cityLondon
dc.identifier.doi10.32996/ijllt.2022.5.12.6
dc.identifier.elaba148057680


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