Human sentiment annotation for isiXhosa and isiZulu.
<p>Human sentiment annotation for isiXhosa and isiZulu.</p>
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , |
| منشور في: |
2025
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| الموضوعات: | |
| الوسوم: |
إضافة وسم
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| _version_ | 1852019613525606400 |
|---|---|
| author | Koena Ronny Mabokela (21492394) |
| author2 | Mpho Primus (21492397) Turgay Celik (14378019) |
| author2_role | author author |
| author_facet | Koena Ronny Mabokela (21492394) Mpho Primus (21492397) Turgay Celik (14378019) |
| author_role | author |
| dc.creator.none.fl_str_mv | Koena Ronny Mabokela (21492394) Mpho Primus (21492397) Turgay Celik (14378019) |
| dc.date.none.fl_str_mv | 2025-06-05T17:33:58Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0325102.t005 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/Human_sentiment_annotation_for_isiXhosa_and_isiZulu_/29248513 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Ecology Sociology Immunology Science Policy Biological Sciences not elsewhere classified population without access leverage existing plms twitter sentiment dataset african languages poses advancing sentiment analysis trained language models div >< p related languages achieved existing multilingual plms sentiment analysis related languages labelled dataset multilingual plms multilingual pre developing plms resource languages native languages world ’ work expands tswana ), task adaptation specific task significant portion setswana </ sesotho </ sepedi </ safrisenti </ promising approach paper explores large data isizulu </ isixhosa </ gap leaves findings demonstrate avoiding training alternative solution 63 %. |
| dc.title.none.fl_str_mv | Human sentiment annotation for isiXhosa and isiZulu. |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | <p>Human sentiment annotation for isiXhosa and isiZulu.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_c6c1bc7113000eccc8a7fddfce586fdb |
| identifier_str_mv | 10.1371/journal.pone.0325102.t005 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/29248513 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Human sentiment annotation for isiXhosa and isiZulu.Koena Ronny Mabokela (21492394)Mpho Primus (21492397)Turgay Celik (14378019)EcologySociologyImmunologyScience PolicyBiological Sciences not elsewhere classifiedpopulation without accessleverage existing plmstwitter sentiment datasetafrican languages posesadvancing sentiment analysistrained language modelsdiv >< prelated languages achievedexisting multilingual plmssentiment analysisrelated languageslabelled datasetmultilingual plmsmultilingual predeveloping plmsresource languagesnative languagesworld ’work expandstswana ),task adaptationspecific tasksignificant portionsetswana </sesotho </sepedi </safrisenti </promising approachpaper exploreslarge dataisizulu </isixhosa </gap leavesfindings demonstrateavoiding trainingalternative solution63 %.<p>Human sentiment annotation for isiXhosa and isiZulu.</p>2025-06-05T17:33:58ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0325102.t005https://figshare.com/articles/dataset/Human_sentiment_annotation_for_isiXhosa_and_isiZulu_/29248513CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/292485132025-06-05T17:33:58Z |
| spellingShingle | Human sentiment annotation for isiXhosa and isiZulu. Koena Ronny Mabokela (21492394) Ecology Sociology Immunology Science Policy Biological Sciences not elsewhere classified population without access leverage existing plms twitter sentiment dataset african languages poses advancing sentiment analysis trained language models div >< p related languages achieved existing multilingual plms sentiment analysis related languages labelled dataset multilingual plms multilingual pre developing plms resource languages native languages world ’ work expands tswana ), task adaptation specific task significant portion setswana </ sesotho </ sepedi </ safrisenti </ promising approach paper explores large data isizulu </ isixhosa </ gap leaves findings demonstrate avoiding training alternative solution 63 %. |
| status_str | publishedVersion |
| title | Human sentiment annotation for isiXhosa and isiZulu. |
| title_full | Human sentiment annotation for isiXhosa and isiZulu. |
| title_fullStr | Human sentiment annotation for isiXhosa and isiZulu. |
| title_full_unstemmed | Human sentiment annotation for isiXhosa and isiZulu. |
| title_short | Human sentiment annotation for isiXhosa and isiZulu. |
| title_sort | Human sentiment annotation for isiXhosa and isiZulu. |
| topic | Ecology Sociology Immunology Science Policy Biological Sciences not elsewhere classified population without access leverage existing plms twitter sentiment dataset african languages poses advancing sentiment analysis trained language models div >< p related languages achieved existing multilingual plms sentiment analysis related languages labelled dataset multilingual plms multilingual pre developing plms resource languages native languages world ’ work expands tswana ), task adaptation specific task significant portion setswana </ sesotho </ sepedi </ safrisenti </ promising approach paper explores large data isizulu </ isixhosa </ gap leaves findings demonstrate avoiding training alternative solution 63 %. |