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BMC Public Health
Published in: BMC Public Health 1/2024

Open Access 01-12-2024 | Research

Analysis of the hikikomori phenomenon – an international infodemiology study of Twitter data in Portuguese

Authors: Francisca Correia Lopes, Mariana Pinto da Costa, Cesar I Fernandez-Lazaro, Francisco J Lara-Abelenda, Victor Pereira-Sanchez, Alan R Teo, Miguel Angel Alvarez-Mon

Published in: BMC Public Health | Issue 1/2024

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Abstract

Background

Hikikomori refers to the extreme isolation of individuals in their own homes, lasting at least six months. In recent years social isolation has become an important clinical, social, and public health problem, with increased awareness of hikikomori around the globe. Portuguese is one of the six most spoken languages in the world, but no studies have analysed the content regarding this phenomenon expressed in Portuguese.

Objective

To explore the hikikomori phenomenon on Twitter in Portuguese, utilising a mixed-methods approach encompassing content analysis, emotional analysis, and correlation analysis.

Methods

A mixed methods analysis of all publicly available tweets in the Portuguese language using a specific keyword (hikikomori) between 1st January 2008 and 19th October 2022. The content analysis involved categorising tweets based on tone, content, and user types, while correlation analysis was used to investigate user engagement and geographical distribution. Statistical analysis and artificial intelligence were employed to classify and interpret the tweet data.

Results

Among the total of 13,915 tweets generated, in terms of tone 10,731 were classified as “negative”, and 3184 as “positive”. Regarding content, “curiosities” was the most posted, as well as the most retweeted and liked topic. Worldwide, most of the hikikomori related tweets in Portuguese were posted in Europe, while “individuals with hikikomori” were the users most active posting. Regarding emotion analysis, the majority of tweets were “neutral”.

Conclusions

These findings show the global prevalence of the discourse on hikikomori phenomenon among Portuguese speakers. It also indicates an increase in the number of tweets on this topic in certain continents over the years. These findings can contribute to developing specific interventions, support networks, and awareness-raising campaigns for affected individuals.
Glossary
Hikikomori
Term used to describe the social phenomenon of individuals, often young adults, who withdraw from social life and isolate themselves at home for a prolonged period, avoiding social interaction.
Infodemiology
Refers to the study of how information spreads and impacts public health, especially on the internet. Analyses patterns of information disclosure to understand how it affects people's knowledge and behaviour.
Machine Learning
Subset of artificial intelligence that involves the development of algorithms and statistical models that enable computers to perform tasks without explicit programming. It relies on patterns and inference from data to improve performance over time.
Deep Learning
A specialised area of machine learning that involves using neural networks with multiple layers (deep neural networks) to model and solve complex problems. It is particularly effective in tasks such as image and speech recognition.
BERTweet
Natural language processing model based on BERT (Bidirectional Encoder Representations from Transformers) architecture, specifically tailored for processing and understanding Twitter data. It enhances language understanding in a social media context.
Emotion-English-Distilroberta-Base
Pre-trained language model based on the Distilroberta architecture, specialised in recognizing and understanding emotions in English text. It is trained to analyse and categorise emotions expressed in written content.
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Metadata
Title
Analysis of the hikikomori phenomenon – an international infodemiology study of Twitter data in Portuguese
Authors
Francisca Correia Lopes
Mariana Pinto da Costa
Cesar I Fernandez-Lazaro
Francisco J Lara-Abelenda
Victor Pereira-Sanchez
Alan R Teo
Miguel Angel Alvarez-Mon
Publication date
01-12-2024
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2024
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-023-17617-0

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