In almost every discussion about the usage of the internet and digital technologies, we can hear diverse opinions on the nature of online interaction. While some herald the multiple opportunities as reflected in the plentitude of channels and social media platforms, others are more guarded, stressing that the online interaction lacks something essential they experience offline. In these debates, the term anonymity often appears, seen both positively, as an opportunity for open self-expression, and negatively, as a factor underlying aggression. For years, anonymity has been used to both specify the unique character of online interaction and differentiate it from offline conditions.

As a researcher on online aggression, I refer to anonymity in explanations of behaviors such as cyberbullying or cyberhate. Anonymity is central for prominent theoretical explanations focusing on online aggression, namely the online disinhibition effect and the Social Identity Model of Deindividuation Effects (Spears, 2017; Suler, 2004). However, from the early years of my research, I have been also puzzled by the term “anonymity,” and how I should approach and apply it in my research. We are living in the age of social media, filled with many types of personal information and materials. We interact using our profiles, with people that know us offline. We see continuing augmentations of online and offline social spaces. In these conditions, what does anonymity actually mean? Should we even still use this term? 

In this article, I summarize several salient points pertaining to the approach to anonymity taken in research. In doing so I draw from prior literature, especially Scott’s seminal work on anonymity (Scott, 1998; 1999; Scott & Rains, 2020). 

In prior computer-mediated communications (CMC) studies, anonymity is often presumed to be equal to a specific (usually single) condition or modality of communication, for example, the invisibility of interacting partners (e.g., Misoch, 2015) or the absence of personal identifying information (e.g., Moore et al., 2012). Such an approach is highly understandable, especially in experimental studies where anonymity is manipulated as a factor. However, we can lose a lot of information by using a single indicator. For example, Lapidot-Lefler and Barak (2012) used an experimental design to examine the effects of factors that could lead to online flaming behaviors, where they indicated and manipulated anonymity using participants’ identification information (i.e., alias versus individual identification details). But, using the webcam, authors also manipulated visibility (i.e., a factor in numerous studies used to manipulate anonymity), and, via additional webcam, also manipulated eye contact, though they did not label these as measures of anonymity. Their results showed differentiated effects of these factors. However, these same factors have been used as single indicators of anonymity in other studies. Acknowledging this issue, Lapidot-Lefler and Barak offer a highly informative discussion about conditions creating an online sense of unidentifiability.

The use of different indicators for anonymity by investigators is linked to its problematic conceptualization as a unidimensional construct. Very often, it is (even implicitly) seen as a lack of a link to identity or an absence of identifiability–which are both multidimensional constructs. Recognizing the complexity of the construct suggests that unidimensional conceptualizations of anonymity are limited. As Marx (1999) stated, anonymity is “one polar value of a broad dimension of identifiability versus nonidentifiability. To be fully anonymous means that a person cannot be identified according to any of the seven dimensions of identity knowledge” (p. 100). Such multidimensional considerations in defining anonymity are usually missing in CMC research. As a result, there is a strong tension between the complex and multidimensional character of the concept, which is reflected in diverse disciplines (such as in research on identity, Kennedy, 2006) and the reductive understanding of anonymity in research on CMC. 

Also, current approaches often view anonymity as a dichotomous construct, that is, it is either present or not (Kennedy, 2006; Scott & Rains, 2020). This approach is hardly applicable in the current media environment with its mix of interaction modalities and the amount of identifying information available. However, adopting the perspective of anonymity as a scale (or series of qualitatively different states) might help explain different states and conditions in which people interact without being reductive in our presumption that anonymity either “is there or not.”

This leads me to the final salient point that anonymity, a currently vaguely defined and insufficiently measured concept, is rather presumed. We need to consider that people perceive themselves—and others—as anonymous to different degrees, depending on various individual and contextual factors. Thus, especially in studies in psychology, it would be highly beneficial to not only measure anonymity in a complex manner but measure its subjective perception by participants in the study. This is not a completely new idea. As early as 1997, Hayne and Rice distinguished technical anonymity, that is removing identifying information, from social anonymity, the perception of users that they are unidentifiable. In my opinion, if we focus on the effects of anonymity on online behaviors, it is the latter that should be at the center of our attention. Yet, so far, at least in research on aggression or other CMC phenomena, there are only a handful of studies that include the measurement of subjective perception of anonymity (see e.g., Hite et al., 2014; Wu & Atkin; 2018). Also, it would be extremely interesting to investigate how this perception forms and what factors, individual and contextual, impact this formation. 

To conclude, there are persisting problems with both the conceptualization and measurement of anonymity. Despite its role in CMC research and common use as an explanatory factor, anonymity remains a rather elusive concept that is under-researched, insufficiently defined, and vaguely used and measured, continually creating a substantial gap in our understanding of CMC and online behaviors. This continues to be a prevailing state in research, even though Scott (1999), more than two decades ago, raised such key issues as the need for a more precise operationalization of anonymity as a continuum, its multidimensional character, and the need to measure subjective perception. On one hand, it is understandable that (analogously to concepts such as “identity”) it is extremely difficult to capture anonymity in research. On the other hand, I believe that we should be careful about the usage of this term, acknowledge its complex nature and pay attention to the level of conceptualization and how it is operationalized in research. Without such operationalization, the nature of the key aspects of CMC will remain hidden.  

References

Hayne, S. C., & Rice, R. E. (1997). Attribution accuracy when using anonymity in group support systems. International Journal of Human-Computer Studies, 47(3), 429–452. https://doi.org/10.1006/ijhc.1997.0134

Hite, D. M., Voelker, T., & Robertson, A. (2014). Measuring perceived anonymity: The development of a context independent instrument. Journal of Methods and Measurement in the Social Sciences, 5(1), 22–39. https://doi.org/10.2458/v5i1.18305

Kennedy, H. (2006). Beyond anonymity, or future directions for internet identity research. New Media & Society, 8(6), 859-876. https://doi.org/10.1177/1461444806069641

Lapidot-Lefler, N., & Barak, A. (2012). Effects of anonymity, invisibility, and lack of eye-contact on toxic online disinhibition. Computers in Human Behavior, 28(2), 434–443. https://doi.org/10.1016/j.chb.2011.10.014

Marx, G. (1999). What’s in a name? Some reflections on the sociology of anonymity. The Information Society, 15(2), 99–112. https://doi.org/10.1080/019722499128565

Misoch, S. (2015). Stranger on the internet: Online self-disclosure and the role of visual anonymity. Computers in Human Behavior, 48, 535–541. https://doi.org/10.1016/j.chb.2015.02.027

Moore, M. J., Nakano, T., Enomoto, A., & Suda, T. (2012). Anonymity and roles associate with aggressive posts in an online forum. Computers in Human Behavior, 28(3), 861–867. https://doi.org/10.1016/j.chb.2011.12.005

Scott, C. R. (1998). To reveal or not to reveal: A theoretical model of anonymous communication. Communication Theory, 8(4), 381–407. https://doi.org/10.1111/j.1468-2885.1998.tb00226.x

Scott, C. R. (1999). The impact of physical and discursive anonymity on group members’ multiple identifications during computer-supported decision making. Western Journal of Communication, 63(4), 456–487. https://doi.org/10.1080/10570319909374654

Scott, C. R., & Rains, S. A. (2020). (Dis)connections in anonymous communication theory: Exploring conceptualizations of anonymity in communication research. Annals of the International Communication Association, 44(4), 385–400. https://doi.org/10.1080/23808985.2020.1843367

Spears, R. (2017). Social identity model of deindividuation effects. In P. Rössler, C. A. Hoffner & L. Zoonen (Eds.) The international encyclopedia of media effects (pp. 1–9). John Wiley & Sons. https://doi.org/10.1002/9781118783764.wbieme0091

Suler, J. (2004). The online disinhibition effect. CyberPsychology & Behavior, 7(3), 321–326. https://doi.org/10.1089/1094931041291295

Wu, T. Y., & Atkin, D. J. (2018). To comment or not to comment: Examining the influences of anonymity and social support on one’s willingness to express in online news discussions. New Media & Society, 20(12), 4512–4532. https://doi.org/10.1177/1461444818776629

(Editors’ Note: Hana Machackova received the 2022 Early Professional Contributions to Media Psychology and Technology of the APA Society for Media Psychology and Technology.)