2026-08-16T03:39:10Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:14548 2024-03-06T10:31:25Z ddc:004 open_access

Supporting the Annotation Experience Through CorEx and Word Mover’s Distance Pecòre, Stefania topic retrieval annotation eating disorders natural language processing Online communities can be used to promote destructive behaviours, as in pro-Eating Disorder (ED) communities. Research needs annotated data to study these phenomena. Even though many platforms have already moderated this type of content, Twitter has not, and it can still be used for research purposes. In this paper, we unveiled emojis, words, and uncommon linguistic patterns within the ED Twitter community by using the Correlation Explanation (CorEx) algorithm on unstructured and non-annotated data to retrieve the topics. Then we annotated the dataset following these topics. We analysed then the use of CorEx and Word Mover’s Distance to retrieve automatically similar new sentences and augment the annotated dataset. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Stefania Pecòre 2021 Is Part Of OASIcs, Volume 93, 3rd Conference on Language, Data and Knowledge (LDK 2021) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.LDK.2021.12 urn:nbn:de:0030-drops-145481 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.LDK.2021.12 eng https://creativecommons.org/licenses/by/4.0/legalcode