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The social identity model of deindividuation effects (or SIDE model) is a theory developed in social psychology and communication studies. SIDE explains the effects of anonymity and identifiability on group behavior. It has become one of several theories of technology that describe social effects of computer-mediated communication.
This anonymity is an important factor in crowd psychology, and behavior in situations such as a riot. This perceived anonymity can be compromised by technologies such as photography . Groupthink behavior and conformity are also considered to be an established effect of internet anonymity.
Hyman Gross suggested that, without privacy—solitude, anonymity, and temporary releases from social roles—individuals would be unable to freely express themselves and to engage in self-discovery and self-criticism. [127] Such self-discovery and self-criticism contributes to one's understanding of oneself and shapes one's sense of identity ...
In contemporary social psychology, deindividuation refers to a diminishing of one's sense of individuality that occurs with behavior disjointed from personal or social standards of conduct. For example, someone who is an anonymous member of a mob will be more likely to act violently toward a police officer than a known individual. In one sense ...
The online disinhibition effect refers to the lack of restraint one feels when communicating online in comparison to communicating in-person. [1] People tend to feel safer saying things online that they would not say in real life because they have the ability to remain completely anonymous and invisible when on particular websites, and as a result, free from potential consequences. [2]
Contrary to anonymity, it has been shown that if one can utilise technology to prevent anonymity, it can further prevent diffusion of responsibility. Studies have shown that if emails are sent directly to individuals as opposed to addressing individuals in mass emails, they can prevent diffusion of responsibility and elicit more responses.
In other words, the desired privacy level changes with time according to environment. Therefore, we might want to avoid people at a particular time but desire contact at another time. Altman also believes the goal of privacy regulation is to achieve the optimum level of privacy (i.e., the ideal level of social interaction). [1]
For example, data produced during human subject research might be de-identified to preserve the privacy of research participants. Biological data may be de-identified in order to comply with HIPAA regulations that define and stipulate patient privacy laws.