Detection of suicide ideation in twitter using ann

dc.contributor.authorYatapala, KDYHT
dc.contributor.authorKumara, BTGS
dc.contributor.editorGanegoda, GU
dc.contributor.editorMahadewa, KT
dc.date.accessioned2022-11-10T03:16:03Z
dc.date.available2022-11-10T03:16:03Z
dc.date.issued2021-12
dc.description.abstractSuicide is considered one of the leading problems in the present. Detecting suicide earlier and providing a solution is considered the most successful way to suicide ideation and suicide attempts prevention. At present, online communication channels are used to express the suicidal tendencies of some people. This paper presents a machine learning approach to identify suicide pattern and detect suicide ideation or thoughts by considering online user-generated content with the aim of suicide ideation detection. People who have suicidal ideations, express strong negative feelings. Here, an Artificial Neural Network is used as a machine learning algorithm. To detect ideations of suicide, we generate feature vectors using different techniques including Word2Vec, Doc2Vec, and TF-IDF features. As the online user communication channel, we select Twitter.en_US
dc.identifier.citationK. Y. D. H. T. Yatapala and B. T. G. S. Kumara, "Detection of Suicide Ideation in Twitter using ANN," 2021 6th International Conference on Information Technology Research (ICITR), 2021, pp. 1-5, doi: 10.1109/ICITR54349.2021.9657404.en_US
dc.identifier.conference6th International Conference in Information Technology Research 2021en_US
dc.identifier.departmentInformation Technology Research Unit, Faculty of Information Technology, University of Moratuwa.en_US
dc.identifier.doidoi: 10.1109/ICITR54349.2021.9657404en_US
dc.identifier.facultyITen_US
dc.identifier.placeMoratuwa, Sri Lankaen_US
dc.identifier.proceedingProceedings of the 6th International Conference in Information Technology Research 2021en_US
dc.identifier.urihttp://dl.lib.uom.lk/handle/123/19457
dc.identifier.year2021en_US
dc.language.isoenen_US
dc.publisherFaculty of Information Technology, University of Moratuwa.en_US
dc.relation.urihttps://ieeexplore.ieee.org/document/9657404en_US
dc.subjectSuicide ideationen_US
dc.subjectData miningen_US
dc.subjectNeural networken_US
dc.subjectTwitteren_US
dc.subjectWord2Vecen_US
dc.titleDetection of suicide ideation in twitter using annen_US
dc.typeConference-Full-texten_US

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