A 2017 review article noted the "cultural norm" among adolescence of being always on or connected to social<unk> , remarking that this reflects young people's "need to belong" and stay up-to-date, and that this perpetuates a "fear of missing out". Other motivations include information seeking and identity formation, as well as voyeurism and cyber-stalking. For some individuals, social<unk>  can become "the single most important activity that they engage in". This can be related to Maslow's hierarchy of needs, with basic human needs often met from social<unk> . Positive-outcome expectations and limited self-control of social<unk> <unk>  can develop into "addictive" social<unk> <unk> . Further<unk> <unk>  may occur when social<unk>  is<unk> d to cope with psychological stress, or a perceived inability to cope with life demands. Cultural anthropologist Natasha Dow Schüll noted parallels to the gambling industry inherent in the design of various social<unk>  sites, with "'ludic loops' or repeated cycles of uncertainty, anticipation and feedback" potentially contributing to<unk> . Another factor directly facilitating the development of addiction towards social<unk>  is implicit attitude towards the IT artifact. Mark D. Griffiths, a chartered psychologist focusing on the field of behavioral addictions, also postulated in 2014 that social networking online may fulfill basic evolutionary drives in the wake of mass urbanization worldwide. The basic psychological needs of "secure, predictable community life that evolved over millions of years" remain unchanged, leading some to find online communities to cope with the new individualized way of life in some modern societies. According to Andreassen, empirical research indicate that addiction to social<unk>  is triggered by the dispositional factors (such as personality, desires, self-esteem), but specific socio-cultural and behavioral reinforcement factors remain to be investigated empirically. A secondary analysis of a large English cross-sectional survey of 12,866 13 to 16 year olds published in Lancet found that mental health outcomes<unk> <unk>  of social<unk>  platforms may be in part due to exposure to cyberbullying, as well as displacement in sleep architecture and physical exercise, especially in girls. Through cyberbullying and discrimination researchers have found that depression rates among teens have drastically increased. In a study done of 1,464 random<unk> rs on Twitter, 64% of those people were depressed, while the majority of depressed<unk> rs were in between 11 and 20. The study was associated with a lack of confidence due to stigma for those who were depressed. In fact out of the 64% that were depressed, over 90% of them were extremely low in profile images and shared<unk> . Moreover, the study also found a strong correlation between the female gender and expression of depression, concluding that the female-to-male ratio is 2:1 for major depressive disorder. In 2018, Harvard University neurobiology research technician Trevor Haynes postulated that social<unk>  may stimulate the reward pathway in the brain. An ex-Facebook executive, Sean Parker, has also espoused this theory. Six Key Mechanisms There are six key mechanisms attributed to the addictive nature of social<unk>  and messaging platforms. Endless scrolling / streaming To attract maximum<unk> r attention, app developers distort time by affecting the 'flow' of content when scrolling. This distortion makes it difficult for<unk> rs to recognize the length of time they spend on social<unk> . Principles similar to Skinner's variable-ratio conditioning can be found with the intermittent release of rewarding reinforcement in an unpredictable stream of 'bad' content. This makes extinguishing behavioral conditioning difficult. Behavioral conditioning is also achieved via the 'auto-play' default of streaming platforms. The more absorbed the viewer becomes, the more time-distortion occurs making it more difficult to stop watching. This is further coupled with minimal time to cancel the next stream thereby creating a false sense of urgency followed by an absorbing relief. Endowment effect / Exposure effect Investing time in social<unk>  platforms generates an emotional attachment to the virtual setting the<unk> r creates. The<unk> r values this above its actual value, which is referred to as the endowment effect. The more time a person spends curating their social<unk>  presence, the more difficult it is for them to give up social<unk>  as they have placed an emotional value on this virtual existence higher than its actual value. The<unk> r is more prone to loss aversion from this endowment. As a result, they are less willing to stop their<unk>  of social<unk> . This is further compounded by the mere exposure the<unk> r has to the respective platforms. This exposure effect suggests repeated exposure to a distinct stimulus by the<unk> r will condition the<unk> r into an enhanced or improved attitude towards it. With social<unk> , repetitive exposure to the platforms improves the<unk> r’s attitude about them. The advertising industry has recognized this potential but rarely<unk> d it due to their belief in an inherent confliction between overexposure and the law of familiarity. The more mere exposure a<unk> r has to a social<unk>  platform, the more they like to<unk>  it. This makes the act of removing social<unk> <unk>  thereby highlighting the effect’s contribution to social<unk> ’s addictive nature. Social Pressures Social<unk>  has developed expectations of immediacy which then create social pressures. One study into the social pressures created from the instant messaging platform, WhatsApp, showed the "Last Seen" feature contributed to the expectation of a fast response. This feature serves as an “automatic approximation of availability” thereby denoting a time frame by which the sender is aware the receiver will reply in and similarly a time frame the receiver must reply in without causing tensions to their relationship. This was further seen in the "Read Receipt" (in the form of ticks) feature on WhatsApp. The nudge of a double tick highlights the reception of the message therefore the sender is consciously aware that the receiver has likely seen the message. The receiver would equally feel pressure to respond fast for fear of violating the sender’s expectation. Since both sides know the working mechanics of the Last Seen and Read Receipt features, a social pressure in the speed of response is created. The effect of this has been linked to an addictive nature of the features as it offers a possible explanation for frequent checking for notifications. Furthermore, it has also been suggested to undermine well-being. Personalized Newsfeed Google is the first tech firm to adopt the personalization of<unk> r content. The company does this by tracking: “search history, click history, location on Google and on other websites, language search query, choice of web browser and operating system, social connections, and time taken to make search decisions.” Facebook similarly adopted this method in their recording of<unk> r endorsement through the "Like" and react options. Facebook’s personalization mechanics are so precise they are capable of tracking the mood of their<unk> rs. The overall effect of this is that it creates “highly interesting, personalized websites” tailored to each<unk> r which in turn leads to more time online and further increases the chances of the<unk> r developing an addictive or<unk>  behavior with social<unk> . Social Rewards and Social Comparisons The "Like" mechanism is another example of social<unk> 's<unk>  features. It is a social cue that visually represents the social validation the<unk> r either gives or receives. One study explored the quantifiable and qualitative effects the "Like" button had on social endorsement. The study asked 39 adolescents to submit their own Instagram photos alongside neutral and risky photos which were then reproduced into a testing app that controlled the number of likes the photo would initially receive prior to testing. The result found adolescents were more likely to endorse both risky and neutral photos if they had more likes. Furthermore, the study suggested that adolescents were more inclined to perceive a qualitative effect of the photos depending on the strength of peer endorsement. Whilst “quantifiable social endorsement is a relatively new phenomenon,” this study is suggestive of the effects the "Like" option as a social cue has on adolescents. Another study looking at different types, three modalities (social interaction, simulation, and search for relations) and two genders (male and female) assessed whether self-esteem contributed to Facebook<unk>  in the context of a social comparison variable. Males were found to have less of a social comparison orientation between the tested contribution however their self-esteem and length of time on Facebook was found to have a negative link. For females, social comparison was the primary factor in the relationship between self-esteem and Facebook<unk> : “females with low self-esteem seem to spend more time on Facebook in order to compare themselves to others and possibly increase their self-esteem, since social comparison serves the function of self-enhancement and self-improvement.” In accordance with the individual traits being tested, the study highlights the tendency to socially compare and its relationship with self-esteem and the length of Facebook<unk> . Zeigarnik Effect / Ovsiankina Effect The Zeigarnik Effect suggests the human brain will continue to pursue an unfinished task until a satisfying closure. The endless nature of social<unk>  platforms affects this effect as they prevent the<unk> r from
Problematic social media use
Problematic smartphone use
Video game addiction
Psychological effects of Internet use
Computer addiction
Factitious disorder imposed on another
Childhood trauma
Social isolation