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Hikikomori is a severe form of social withdrawal, originally described in Japan but recently reported in other countries. Debate exists as to what extent hikikomori is viewed as a problem outside of the Japanese context.
We aimed to explore perceptions about hikikomori outside Japan by analyzing Western language content from the popular social media platform, Twitter.
We conducted a mixed methods analysis of all publicly available tweets using the hashtag #hikikomori between February 1 and August 16, 2018, in 5 Western languages (Catalan, English, French, Italian, and Spanish). Tweets were first classified as to whether they described hikikomori as a problem or a nonproblematic phenomenon. Tweets regarding hikikomori as a problem were then subclassified in terms of the type of problem (medical, social, or anecdotal) they referred to, and we marked if they referenced scientific publications or the presence of hikikomori in countries other than Japan. We also examined measures of interest in content related to hikikomori, including retweets, likes, and associated hashtags.
A total of 1042 tweets used #hikikomori, and 656 (62.3%) were included in the content analysis. Most of the included tweets were written in English (44.20%) and Italian (34.16%), and a majority (56.70%) discussed hikikomori as a problem. Tweets referencing scientific publications (3.96%) and hikikomori as present in countries other than Japan (13.57%) were less common. Tweets mentioning hikikomori outside Japan were statistically more likely to be retweeted (
Hikikomori is a repeated word in non-Japanese Western languages on Twitter, suggesting the presence of hikikomori in countries outside Japan. Most tweets treat hikikomori as a problem, but the ways they post about it are highly heterogeneous.
This concept was developed in the last decades of the 20th century in Japan [
In recent years, clinicians and researchers across the world have reported the existence of patients with similar patterns of severe social withdrawal [
Despite the growing observation of hikikomori globally, there has been an alternative viewpoint that hikikomori does not represent a form of psychopathology; rather, it should be considered a
Individuals with
Twitter is one of the most popular social media platforms in Western countries and allows users to publicly share and interact with short posts (tweets) [
The primary aims of this study are to (1) describe and categorize the content of tweets regarding hikikomori in several Western languages; (2) identify what content related to hikikomori generates the most interest (retweets, likes, and associated hashtags); and (3) explore temporal trends in hikikomori on Twitter.
This study was designed as a mixed methods analysis of quantitative Twitter metrics and qualitative content from recent publicly available tweets about hikikomori in languages used in Western countries where hikikomori has been described. The inclusion criteria for tweets were (1) being public (nonprivate); (2) use of the hashtag #hikikomori; (3) posted between February 1 and August 16, 2018; and (4) text in English, Italian, Spanish, Catalan, or French. The exclusion criteria were (1) no identifiable language or (2) only contained a link (ie, spam tweets).
Twitter provides 3 primary sources of data: Twitter’s Search application programming interface (API), Twitter’s Streaming API, and Twitter’s Firehose. Twitter’s Firehose is the only one that has access to 100% of Twitter content. Twitter’s Firehose formerly was handled by multiple data providers (eg, Gnip, DataSift, and Topsy), although, since August 2015, Twitter only allows access to Twitter’s Firehose through Gnip [
All the retrieved tweets were directly inspected by 2 raters fluent in the included languages (VPS and MAM): both of them were psychiatric trainees and had previous experience in Twitter-related research, including the analysis of tweets. First, we scanned all of the tweets to classify them by language and excluded 386 of the total of 1042 tweets, according to our exclusion criteria. We created a codebook based on our research questions, previous experience analyzing tweets, and also determined by the most common themes we had observed reading the tweets. VPS and MAM analyzed 252 tweets separately to test the codebook. After an agreement on the codebook, the 2 raters classified, independently, a random set of 80 tweets (40 in English and 40 in Spanish), and the interrater reliability between both raters was assessed obtaining Kappa values ranging from 0.28 to 0.83 for the different categories and subcategories. Discrepancies were discussed between the raters and with the senior author (AT), and after revising the codebook, the interrater reliability was reassessed with a different set of 80 randomly selected tweets (40 in English and 40 in Spanish). As this resulted in adequate Kappa values ranging from 0.71 to 1.00 [
Flowchart of data management and content analysis.
Category and subcategory definitions and examples of classification. Links and usernames within the tweets have been removed (usernames and personal names were replaced by XXXX). To seek for clarity, all the tweets reported here are in English (when tweets in other languages are reported, an English translation prepared by us is included in parentheses).
Category (or subcategory) | Definition | Examples of tweets | |
Unclassifiable | Not enough information, only links, spam, or random content. | “Furries is Love Furries is Life #Furries #Hikikomori”; “damn... that’s why I play this game again... kawaii character :D; #WhoCares #Lunatic #Hikikomori” | |
Hikikomori not as a problem | Positive or indifferent thoughts, attitudes, or behaviors related to hikikomori. | “I'm a hikikomori but I think outside the room. But many extroverts think like birds in a cage. #hikikomori”; “About to go full #Hikikomori. No regrets” | |
Medical | Medical publications or reports, or events, campaigns, or interventions that present data or information related to hikikomori. | “Can we use #SocialMedia to identify socially withdrawn youth in China? Our latest paper on #hikikomori now out in @XXXX”; “#japan, Doctors began to observe it in the mid-1980s, with young men suffering from lethargy and refusing to communicate -- #hikikomori an insight #psychological ailment”. | |
Anecdotes | Personal stories, testimonials, or third-person reports of people with hikikomori or related behaviors. | “#Hikikomori literally means ‘withdrawal from others’ in Japanese—follow the stories of a family affected by this modern-age social phenomenon as one day Nils decides to hide in his room and never leave. #Week53”. | |
Social | Socially oriented issues related to hikikomori, including antistigma events, provision of social support, or related activities. | “If you are experiencing #hikikomori chat to others on #joinin247 #london #tokyo #osaka #kyoto #isolation #youarenotalone #endthesilence” | |
Scientific reference | Explicit reference to a scientific publication (paper, presentation) in tweets with hikikomori as a problem. | “Can we use #SocialMedia to identify socially withdrawn youth in China? Our latest paper on #hikikomori now out in @XXXX”; “Secure Base Script and Psychological Dysfunction in Japanese Young Adults (Umemura et al 2018) #hikikomori via @XXXX” | |
Other country | Explicit reference to hikikomori as a problem in a country other than Japan. | “#Hikikomori, è boom anche in Italia: migliaia di giovani si auto-recludono in casa”. (“#Hikikomori is also a boom in Italy: thousands of youth are self-reclusive at home”); “Can we use #SocialMedia to identify socially withdrawn youth in China? Our latest paper on #hikikomori now out in @XXXX”. |
All the tweets were statistically analyzed to describe the number of tweets, retweets, and likes per language and category (and subcategory), considering retweets and likes as indices for reflecting the users’ interests in particular topics. We had previously reported the value of retweets in this regard [
This study received the approval of the University of Navarra Research Ethics Committee (October 11, 2018, modified on December 13, 2018) and is compliant with the research ethics principles of the Declaration of Helsinki (seventh revision, 2013). This study did not directly involve human subjects, nor did it include any intervention; instead uses only publicly available tweets (subject to universal access through the internet according to the Terms of Service that all users in Twitter accept). Nevertheless, we have taken care to not directly reveal in this report any username, and we have avoided citing tweets that could be offensive or compromised to someone.
Our search tool provided 1042 original tweets using #hikikomori in the established period, with 1433 retweets, a potential reach of 7,974,329, 10,613,856 potential impacts, and 908 contributors (ie, total number of different users posting with a given hashtag). As shown in
The probability of retweet and like per category and subcategory is presented in
Descriptive characteristics of the original tweets included in the analysis, categorized by total amount per language and category. For each language and category or subcategory, total number of tweets (n) and relative proportions (%) are provided. In the first row, percentages of the total tweets in each language is calculated over the total of included tweets (ie, percentage of tweets in a given language among the total number of included tweets, 656); in the following rows, percentages are calculated for each category over the figures in the first row and in the same column (ie, percentage of tweets from a category among the total tweets in the given language or percentage of total tweets in each category among the total number of included tweets). Percentages are rounded to two decimals.
Category | English, n (%) | Italian, n (%) | Spanish and Catalan, n (%) | French, n (%) | Total, n (%) | |
Total tweets | 290 (44.2) | 211 (32.16) | 61 (9.29) | 94 (14.32) | 656 (100) | |
Unclassifiable | 125 (43.1) | 54 (25.56) | 19 (31.14) | 37 (39.36) | 235 (35.82) | |
Classifiable | 165 (56.89) | 157 (74.44) | 42 (68.86) | 57 (60.64) | 421 (64.18) | |
Not a problem | 30 (10.34) | 0 (0) | 13 (21.31) | 6 (6.38) | 49 (7.46) | |
Any | 132 (45.51) | 156 (73.93) | 29 (47.54) | 51 (54.25) | 372 (56.7) | |
Medical | 79 (27.24) | 132 (62.56) | 19 (31.14) | 47 (50) | 277 (42.22) | |
Anecdotes | 43 (14.83) | 13 (6.16) | 8 (13.11) | 3 (3.19) | 67 (10.21) | |
Social | 10 (3.45) | 11 (5.21) | 2 (3.28) | 1 (1.06) | 24 (3.66) | |
Scientific reference | 18 (6.21) | 5 (2.37) | 1 (1.64) | 2 (2.13) | 26 (3.96) | |
Other country | 16 (5.18) | 64 (30.33) | 2 (3.28) | 7 (7.45) | 89 (13.57) |
World map with countries where the presence of hikikomori was explicitly referenced by the tweets (Italy=63 tweets, United States=7 tweets, France=6 tweets, China=4 tweets, United Kingdom=3 tweets, and South Korea, India, Tunisia, and Spain=1 tweet each).
Retweet to tweet ratio per category and subcategory.
Category and subcategory | Tweets, N | Retweets | Likes | ||||||||||||||||
N | Mean (SD) | Median | N | Mean (SD) | Median | ||||||||||||||
No | 49 | 140 | 2.86 (11.00) | 1 | 171 | 3.49 (16.54) | 0 | ||||||||||||
Yes | 372 | 663 | 1.78 (2.66) | 1 | 507 | 1.36 (3.84) | 0 | ||||||||||||
Medical | 281 | 518 | 1.84 (2.82) | 1 | 379 | 1.35 (4.11) | 0 | ||||||||||||
Anecdotes | 67 | 109 | 1.63 (2.38) | 1 | 110 | 1.64 (3.25) | 0 | ||||||||||||
Social | 24 | 36 | 1.5 (1.10) | 1 | 18 | 0.75 (0.90) | 0.5 | ||||||||||||
No | 346 | 595 | 1.72 (2.67) | 1 | 413 | 1.19 (3.21) | 0 | ||||||||||||
Yes | 26 | 67 | 2.58 (2.56) | 1.5 | 90 | 3.46 (8.46) | 1 | ||||||||||||
No | 283 | 476 | 1.68 (2.81) | 1 | 330 | 1.17 (3.41) | 0 | ||||||||||||
Yes | 91 | 187 | 2.05 (2.11) | 1 | 174 | 1.91 (4.89) | 1 |
aNumber of retweets and likes per category and subcategory of all tweets in the included languages (here not separated by language), along with its mean (SD) and median values. Mann-Whitney
There were no differences in retweets and likes ratios among the different subcategories that considered hikikomori as a problem. The distribution of retweets per language followed an asymmetric distribution, with some individual tweets receiving a large number of retweets and likes; therefore, a statistical comparison of tweets and likes per language would be unreliable. Interestingly, accounting for all the tweets in the sample, and a secondary research result, the indices of retweet and like showed a moderate (Spearman’s rho: 0.54) and significant (
The number of times each hashtag appears is shown in parentheses. Less than 5 are reported if the total number of associated hashtags per language was lesser than that number. More than 5 are reported when a tie occurred. For hashtags in languages other than English, an English translation is provided in parentheses. An interpretation of the hashtags is provided in the Discussion section.
Finally,
Correlation between retweets and likes among all the tweets in the sample (1042), showing a moderate (Spearman's rho: 0.54) and significant (
Top 5 hashtags associated with classifiable #hikikomori tweets, according to the language of the tweet. The values in brackets represent the number of tweets in the sample with the corresponding hashtags.
Language | |
English | #japan (32), #neet (10), #culture (9), #otaku (7), #mentalhealth (7) |
Italian | #giovani (youth) (24), #italia (Italy) (16), giappone (Japan) (9), #isolamento (isolation) (8), #adolescenti (adolescents), #asocialita (asociality), #stareindisparte (being apart) and #autorrecludono (self-reclusion) (5) |
Spanish | #japon (Japan) (5), #psicologia (psychology), #neetlife (4), #depresion (depression), #videojuegos (videogames), #anime, #adiccionalosvideojuegos (addiction to the videogames) (2) |
French | #societe (society) (4), #sante (health) (2) |
a
Time trend of all the tweets with #hikikomori in the period of study. The graph includes the number of contributors (different Twitter users publishing with this hashtag), original tweets, retweets, replies (tweets published as replies to the tweets with the hashtag), links and pictures included, and total number of tweets (original+retweets).
In this study, we investigated the tweets generated about hikikomori in several Indo-European languages (English, Italian, Spanish, Catalan, and French) which are mainly spoken in Western countries and altogether account for more than a billion native speakers. Our analysis strategy with Twitter Firehose data stream allows access to 100% of all public tweets within the search limits of words and time [
To our best knowledge, this is the first study related to hikikomori in Twitter and the first to apply a mixed quantitative-qualitative approach to analyze tweets in different languages. English and Italian were the most used languages among those analyzed. A fair amount of the tweets could not be analyzed, which might be due to lack of information or context, or a random or nonsense use of the word hikikomori (in several cases, probably, as spam). Among the classified tweets, a minority described a perception of hikikomori or related behaviors as nonproblematic, perhaps describing a self-imposed lifestyle. Conversely, the majority of the tweets reported hikikomori as a problem, mainly in general terms (as an alarming social phenomenon or as a psychopathology), and at a lesser extent, some included first- or third-person testimonials, whereas the fewer were related to solidarity/activism. Explicit scientific references were barely found, but more than one-tenth of the tweets reported hikikomori in countries other than Japan, with a striking majority referring to Italy. Among the classifiable tweets, top associated hashtags were mainly related to Japan, the youth, the mental health psychology, and the society and culture. The time trend did not show markedly differentiated peaks of activity related to the hashtag.
Recent publications have proven the role of social media as a target for medical research and interventions [
In addition, Twitter might be considered as an indicator of real-time public opinion [
It should be noted that, currently, the literature related to medical research in hikikomori is also heterogenous and the concept has not yet reached an international consensus regarding its nature as a social phenomenon, a cultural-bond syndrome, or a psychopathological symptom or disorder per se [
Although few tweets included personal testimonies, their existence proves the value of Twitter as a means of communicating this kind of contents to a large public in spite of the still present public and self-stigma toward psychiatric conditions [
The global extension of the hikikomori phenomenon was confirmed in our analysis, as this term was used to name a problem existing in some countries across the world, and, despite the relatively low amount of tweets with these contents, they elicited a significant interest among users, as reflected by their statistically higher chance to be retweeted and liked. The increased interest in the emergence of hikikomori in countries other than Japan (especially in Italy, with some tweets reporting very high figures of prevalence in that country) reflected in retweets and likes of these contents contrasts with the still scarce published scientific literature of hikikomori and the lack of epidemiological figures and intervention guidelines in non-Japanese countries. Twitter is a fast social media reflecting real-time events and opinions; so, despite the heterogeneity and unnacuracy of many contents, clinicians, researchers, and policymakers should take them into account to address the problems and worries reflected in this social media and to rapidly detect and intervene on various health conditions [
We could not futher characterize the contents of the tweets addressing hikikomori as a medical problem, but they included news, epidemiological figures, opinions, research reports, and interventions. It would be valuable to explore the medical contents more in detail and compare them with the Twitter research in other health conditions. In addition, hikikomori’s core symptoms make social media a valuable tool to reach these patients [
In accordance with previous research in Twitter, we considered retweets as a measure of users’ particular interest in a topic, which might be associated to the emotions elicited by the tweets in them [
Some limitations should be noted in this study and need to be discussed in the light of its strengths. Most importantly, the codebook design and text analysis by 2 raters (with a third author as a supervisor), altogether with the mixed nature of this study (with a qualitative plus a quantitative approach), imply a degree of subjectivity, disagreement, and human error and constitute a challenge for its potential reproducibility by other authors. To address this issue, the study comprised a series of steps of initial review, design, and test of pilot codebooks and measurements of the interrater reliability. Thus, the process has been consistent, and the final ratings were expected to be reliable between the 2 raters. Consequently, in our opinion, this methodology is consistent with previous medical research studies in Twitter [
To note, #hikikomori is not probably the unique word used in Twitter to reference this phenomenon (particularly outside Japan, where this concept may be unknown and where other words such as social isolation and withdrawal might be preferred), and tweets in Japanese (where one would expect to find the majority of the contents related to hikikomori) were not considered in this study and thus remain as a source of future cross-cultural research. However, although hikikomori is used as a limited term outside Japan (people might use other words to name it), this concept could also be a potential self-identification term for people who suffer from this problem and have no other words to name it [
The time frame was somewhat arbitrary but was selected to expect a reasonable number of tweets to classify. Apparently, the time trends of the retrieved tweets did not suggest the existence of a clear temporal pattern. A time trend was described in this study to rule out the presence of evident peaks in the activity of Twitter users regarding this topic, which has been observed in other medical conditions such as breast cancer during the so-called
In conclusion, hikikomori is a repeated word in different Western languages in Twitter, and despite its frequent use for uncertain or nonsense purposes, it is markedly perceived as a problem with strong associations with Japan, the society, the youth, and isolation. In addition, Twitter is a means to report personal stories, scientific publications, and the presence of this problem in non-Japanese societies. Our results provide a framework to take advantage of Twitter to provide users with accurate information, fight stigma, and reach a target population which might be unlikely to leave their rooms to ask for help by themselves. These kinds of interventions, using other social media platforms, have started to prove effective in people with hikikomori [
application programming interface
not in employment, education nor training
AT’s work was supported in part by a Career Development Award from the Veterans Health Administration Health Service Research and Development (HSR&D; CDA 14-428). The US Department of Veterans Affairs had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication. The findings and conclusions in this document are those of the authors who are responsible for its contents; the findings and conclusions do not necessarily represent the views of the US Department of Veterans Affairs or the United States government. We want to acknowledge the Japanese Society of Psychiatry and Neurology for the 2018 Fellowship Award granted to VPS and for its encouragement to work on international research studies on hikikomori. Ms Teresa Abrego and Ms Maite Muruzabal, from Tweetbinder, SA, collaborated significantly in the retrieval of tweets through their search engine.
This work was partially supported by grants from the
VPS and MAM participated equally as principal contributors in the research design, content analysis, statistical supervision and manuscript writing, review, and submission. AA conducted and reported the statistical analysis. MA contributed as the reviewer of the manuscript. AT contributed as the main supervisor of all the cited stages, with a special involvement in the study design and manuscript writing.
None declared.