Building a corpus on Eating Disorders from TikTok: challenges and opportunities
Authors: Melissa Donati, Ludovica Polidori, Paola Vernillo, Gloria Gagliardi (Università di Bologna, 2023)
Topic: Sentiment, Emotion, Irony, Hate

Abstract
We present two synchronic corpora of Eating Disorders (ED) related discourse on Social Media. PAC (i.e., ProAna/Anorexia Corpus) and RAC (i.e., Recovery from Ana/Anorexia Corpus) resources focus on the contents posted on TikTok, respectively, by communities promoting anorectic behavior and users sharing experiences concerning the process of recovery from their ED. We report on the corpus statistics and creation process, focusing specifically on the methodological issues raised by this novel Social Media platform.

Introduction
It was only 20 years ago that one of the darkest sides of Eating Disorders (ED) was revealed through the proliferation of websites, blogs, and social networks, in which a growing number of adolescents and young adults started sharing information about their eating experiences with like-minded users. Among these pro-ED communities, researchers and clinicians showed particular concern for pro-Ana (i.e., “pro-anorexia”) groups, i.e., web-based communities of anorexic (or aspiring anorexic) individuals engaged in the promotion of their Eating Disorder [1]. Interestingly, one of the most horrific and dangerous aspects of pro-Ana groups is that Anorexia Nervosa (AN) is not presented as a psychiatric disorder associated with pathological body image dissatisfaction [2], but more as a way of living with its own rules and rituals to be respected. While over the last years, much has been done to prevent the circulation of pro-ED content on social media (e.g., TikTok’s adoption of measures to obscure harmful contents: [3]), a new but specular phenomenon recently took the toll, that is, the spread of pro-recovery accounts of individuals who are in the process of healing from an ED and are willing to share their eating experience to help other online users [4]. From a linguistic perspective, research on ED has been very limited and became an object of study only in recent years [5, 6, 7, 8, 9, 10] as opposed to other psychopathologies, such as schizophrenia [11, 12], personality disorder [13], and depression [14, 15, 16, 17]. This already problematic picture has been further compromised by the inhomogeneous representation of linguistic data in the literature, where the majority of studies have been dedicated to the linguistic profiling of ED-affected individuals in a Germanic language (English, German, Norwegian) [18]. This paper represents a small step towards the reversal of this tendency but a crucial part of two larger projects (Metaphan1 and RaAM project 2022) aiming at identifying, by the adoption of different NLP techniques and tools, potential lexical and semantic patterns in anorectic individuals. To this end, in the current research, we show the data collection process (i.e., oral and written productions) from ED communities on TikTok, currently representing the most widely used social media among young people and adolescents, namely the population groups at greater risk for EDs. In the following paragraphs, we give a brief overview of the literature on the topic (Section 2), then we describe the process of creating the corpus and discuss the methodological issues that were met (Section 3) and to conclude we provide few insights for future works (Section 4).

Conclusion
The aim of this work was twofold: on the one hand, we wanted to present two corpora on EDs, the English pro-Ana corpus (PAC) and the Italian pro-Recovery corpus (RAC), that were both built by extracting data from the popular SM TikTok; on the other, we wanted to discuss some methodological issues related to building a corpus using this platform as a source of data. More specifically, we pointed out that the absence of an official API does not allow the automatic extraction of the videos and requires manual work, which is highly time-consuming and does not allow to collect a very large sample of data. This, in turn, might impede the application of more complex computational analysis and limit the generalizability of the results. In addition, we raised the issue related to the transcription of the videos to text. In this case, implementing automatic approaches is not always feasible because of the extreme visual complexity and variability of TikTok videos. Given the highly interactive nature of this SM and its unprecedented success, we believe that TikTok constitutes an extremely interesting source of linguistic and non-linguistic data that could be used to analyze other complex social and psychological phenomena and we hope that this work paves the way for further research in this direction.