Measuring Digital Social Status

If one person has ten million followers and another has one hundred thousand, which of them has higher digital social status? The answer seems straightforward if we treat follower count as a measure of status. But the question becomes much more difficult if those one hundred thousand followers include the leading specialists in the field, who turn to the account holder for guidance, cite their work, and attach considerable weight to their opinions, while the other person’s millions of followers follow them primarily for entertainment and do not accord them a comparable position within their community. Social media platforms provide us with more numbers than we have ever had before, but the ease of measuring something does not necessarily mean that we are measuring the right thing.

Digital social status is neither fame nor follower count nor the volume of engagement. Rather, it is the relative position that a digital community accords to an individual or institution, together with the recognition, respect, and social weight associated with that position. Status therefore does not exist in a vacuum; it exists within a particular community. A person may enjoy high status among sports content creators, moderate status among sports journalists, and virtually no significant standing within an academic community. Likewise, an institution may be a leading reference point within a particular professional sector without enjoying the same position outside it. This conception comes close to Stanford sociologist Cecilia Ridgeway’s definition of status in 2026 as a relative social ranking manifested in the esteem, respect, deference, and influence that others accord to an individual.

Yet this position cannot be captured by a single metric. In 2024, Tianyu Xu, Blair Evans, and Alex Benson of Canada’s Western University reviewed differing definitions of status and approaches to measuring it in Organizational Psychology Review. They proposed a definition combining respect, admiration, and voluntary deference, while also distinguishing between status as a general judgment about an individual and status that emerges within a relationship between two people. This makes the direct conversion of platform metrics into a measure of status an oversimplification of a much more complex problem.

Follower count tells us about audience size; views tell us about reach; and likes, comments, and shares reflect different forms of engagement. But none of these metrics, on its own, tells us where a community places the account holder relative to others. Ziqiang Hu, Wei Luo, Justin Zhang, and Anna Ginot examined this issue in 2025 in a study published in the Journal of Organizational and End User Computing. By manipulating levels of expertise and follower counts on a hypothetical account on X, they found that greater expertise and larger numbers of followers increased participants’ perceptions of social status and dominance. Here, the distinction between a signal and an outcome becomes important: a number may influence people’s assessment of status, but it does not become status itself.

The same applies to position, wealth, educational qualifications, awards, and prior fame. In 2020, Allison Biancchi and Robert Shelley discussed in Sociological Theory how prior reputations—whether a person is perceived as well-liked or disliked—can accompany them into a new group and activate a process of status generalization. Yet a minister does not necessarily have higher digital social status simply because he or she is a minister; nor does a university professor necessarily have higher status simply because of their academic position; nor does a businessperson necessarily enjoy greater status because they are wealthier. Similarly, a large institution does not automatically have higher status than a smaller institution merely because of its size or history. Such signals may provide an initial advantage, but they do not determine the position that a community ultimately accords to the actor.

Measurement becomes even more difficult when we move from counting relationships to understanding them. In 2012, Michael Sauder, Frieda Lin, and Joel Podolny examined status within and between organizations in the Annual Review of Sociology, highlighting the contribution of network approaches to understanding status positions and hierarchies. Network-analysis measures allow us to examine an actor’s position and the nature of the ties directed toward them rather than merely counting those ties. This opens the door to a more precise question than simply asking how many people interact with you: Who are the people who grant you recognition, and what is their position within the community?

But network centrality is not status either. A highly active person may occupy a central position according to certain network measures without being accorded comparable respect or authority by the community. An institution may have extensive connections because it is larger, older, or possesses formal powers, without that automatically making it the most prestigious institution within its community.

Conversely, a specialist who is relatively inactive—or an institution with limited visibility—may nevertheless be the person or organization to whom members of the field turn for guidance and whom they accord substantial weight. The network therefore reveals one dimension of relationships and position, but it is not sufficient on its own to distinguish status from activity or structural prominence.

This brings part of the measurement process back to the community itself. In 2020, Sio Yu and Gavin Kilduff of New York University demonstrated through four field studies published in the Journal of Personality and Social Psychology that members of a group differ in their perceptions of its status hierarchy, and that those who were more accurate in perceiving that hierarchy tended to communicate with higher-status individuals and performed better.

It is therefore not enough to ask people whom they perceive as having higher status. It is useful to compare their judgments with what they actually do: Whom do they turn to? Whom do they cite? Whose opinion do they seek? And how do these judgments manifest themselves in actual relationships?

The same behavior can be observed among institutions. When an institution becomes a model against which other institutions compare their practices, or a reference point whose tools and resources others rely upon, we capture part of the way in which its professional community treats it. Yet being a reference point or a benchmark is not, by itself, sufficient to establish status, just as an individual’s follower count is not enough. Such indicators acquire meaning only when interpreted alongside the community’s evaluation, the institution’s position relative to others, and the nature of the relationships that form around it.

Time adds another dimension that cannot be ignored. An account that dominates public discussion for a week because of a widely circulated event may experience a rapid increase in its numbers and connections without acquiring stable status. The same may happen to an institution whose visibility suddenly increases because of a campaign, crisis, or major event.

Jeffrey Smith and Robert Faris examined changes in status within adolescent networks in a study published in Social Networks in 2015. They found that individuals move upward and downward within the hierarchy, and that many who rise later lose the status they have gained. Digital social status should therefore not be measured as a snapshot captured at a single moment, but as a position whose transformation and stability are observed over time.

Nor is the platform itself the community. The same specialist may present differently on LinkedIn, X, and TikTok, and an institution’s strength of presence may vary from one platform to another. Yet the actors encountered across these platforms may belong to the same professional community. The most appropriate unit of measurement, therefore, appears to be the specific digital community, with platforms serving as environments in which status becomes visible to varying degrees.

There is no meaningful absolute status score for an individual or institution until we ask: Status among whom?

For this reason, perhaps the greatest mistake would be to begin constructing a digital social-status index by adding followers, views, engagement, and network centrality, assigning weights to each, and producing a score out of 100. We would certainly obtain a number, but we would not know precisely what that number measures.

A more appropriate approach would begin with three intersecting sources: what the community says about the actor’s position, what the community does in relation to that actor, and what the network of relationships reveals. Time would then be introduced to distinguish stable status from temporary prominence.

This could lead to a relative ranking within a community rather than an absolute score—or perhaps to something more useful than a number itself: a map showing where an individual or institution sits within the community, who grants them recognition, how their status manifests itself across platforms, and how it changes over time.

Digital social status is not, at its core, a number. It is a social relationship, and numbers can reveal only some of its characteristics.

Perhaps the real measurement of status begins when we stop asking the platform who has the biggest numbers and start asking the community whose voice carries the greatest weight.