000149145 001__ 149145
000149145 005__ 20251017144647.0
000149145 0247_ $$2doi$$a10.1007/s13278-023-01029-4
000149145 0248_ $$2sideral$$a135385
000149145 037__ $$aART-2023-135385
000149145 041__ $$aeng
000149145 100__ $$0(orcid)0000-0002-7730-8527$$aAguerri, Jesús C.$$uUniversidad de Zaragoza
000149145 245__ $$aOld crimes reported in new bottles: the disclosure of child sexual abuse on Twitter through the case #MeTooInceste
000149145 260__ $$c2023
000149145 5060_ $$aAccess copy available to the general public$$fUnrestricted
000149145 5203_ $$aMovements such as #MeToo have shown how an online trend can become the vehicle for collectively sharing personal experiences of sexual victimisation that often remains unreported to the criminal justice system. These social media trends offer new opportunities to social scientists who investigate complex phenomena that, despite existing since time immemorial, are still taboo and difficult to access. They also bring technical difficulties, as the challenge to identify reports of victimisation, and new questions about the characteristic of the events, the role that victimisation testimonies play and the capacity to detect them by analysing their characteristics. To address these issues, we collected 91,501 tweets under the hashtag #MeTooInceste, posted from the 20 to 27 January 2021. A model was fitted using Latent Dirichlet Allocation that detected 1688 tweets disclosing experiences of child sexual abuse, with an accuracy of 91.3% [± 3%] and a recall of 93.1% [± 5%]. We performed Conjunctive Analysis of Case Configurations on the tweets identified as disclosures of victimisation and found that long tweets posted by users with small accounts, without URL or picture, were more likely to be related to disclosure of child sexual abuse. We discuss the possibilities of these trends and techniques offer for research and practice.
000149145 536__ $$9info:eu-repo/grantAgreement/ES/AEI/PID2021-125731OB-C31$$9info:eu-repo/grantAgreement/ES/MICINN/FJC-2020-042961-I
000149145 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es
000149145 592__ $$a0.667$$b2023
000149145 593__ $$aCommunication$$c2023$$dQ1
000149145 593__ $$aMedia Technology$$c2023$$dQ1
000149145 593__ $$aInformation Systems$$c2023$$dQ2
000149145 593__ $$aComputer Science Applications$$c2023$$dQ2
000149145 593__ $$aHuman-Computer Interaction$$c2023$$dQ2
000149145 594__ $$a5.7$$b2023
000149145 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000149145 700__ $$aMolnar, Lorena
000149145 700__ $$aMiró-Llinares, Fernando
000149145 7102_ $$14009$$2813$$aUniversidad de Zaragoza$$bDpto. Psicología y Sociología$$cÁrea Trabajo Social y Serv.Soc
000149145 773__ $$g13, 1 (2023)$$tSocial Network Analysis and Mining$$x1869-5450
000149145 8564_ $$s743043$$uhttps://zaguan.unizar.es/record/149145/files/texto_completo.pdf$$yVersión publicada
000149145 8564_ $$s2594828$$uhttps://zaguan.unizar.es/record/149145/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000149145 909CO $$ooai:zaguan.unizar.es:149145$$particulos$$pdriver
000149145 951__ $$a2025-10-17-14:34:31
000149145 980__ $$aARTICLE