# Wisdom of the Crowd or Wisdom of a Few? An Analysis of Users' Content Generation

arXiv: https://arxiv.org/abs/1604.03044 · HTML: https://mlsanity.com/paper/1604.03044/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Apr 2016.

## Built on by (most cited first, 1 of 1)

- [Data Augmentation for Fake Reviews Detection in Multiple Languages and Multiple Domains](https://mlsanity.com/paper/2504.06917/) (2025)

## Abstract (arXiv)

In this paper we analyze how user generated content (UGC) is created, challenging the well known it wisdom of crowds concept. Although it is known that user activity in most settings follow a power law, that is, few people do a lot, while most do nothing, there are few studies that characterize well this activity. In our analysis of datasets from two different social networks, Facebook and Twitter, we find that a small percentage of active users and much less of all users represent 50% of the UGC. We also analyze the dynamic behavior of the generation of this content to find that the set of most active users is quite stable in time. Moreover, we study the social graph, finding that those active users are highly connected among them. This implies that most of the wisdom comes from a few users, challenging the independence assumption needed to have a wisdom of crowds. We also address the content that is never seen by any people, which we call digital desert, that challenges the assumption that the content of every person should be taken in account in a collective decision. We also compare our results with Wikipedia data and we address the quality of UGC content using an Amazon dataset. At the end our results are not surprising, as the Web is a reflection of our own society, where economical or political power also is in the hands of minorities.