ArticlePloS one2019
Influence of augmented humans in online interactions during voting events.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed.
- Regional and temporal patterns of partisan polarization during the COVID-19 pandemic in the United States and Canada.PloS one · 2026Article
- A new sociology of humans and machines.Nature human behaviour · 2024Review
- Quantifying the vulnerabilities of the online public square to adversarial manipulation tactics.PNAS nexus · 2024Article
- Article
- Sustainable development goals as unifying narratives in large UK firms' Twitter discussions.Scientific reports · 2023Article
- Detecting bots in social-networks using node and structural embeddings.Journal of big data · 2023Article
- The voice of few, the opinions of many: evidence of social biases in Twitter COVID-19 fake news sharing.Royal Society open science · 2022Article
- Bots are less central than verified accounts during contentious political events.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Italian Twitter semantic network during the Covid-19 epidemic.EPJ data science · 2021Article
- Flow of online misinformation during the peak of the COVID-19 pandemic in Italy.EPJ data science · 2021Article
- Insights into elections: An ensemble bot detection coverage framework applied to the 2018 U.S. midterm elections.PloS one · 2021Article
- How do Twitter users react to TV broadcasts dedicated to vaccines in Italy?European journal of public health · 2020Article
- Early detection of internet trolls: Introducing an algorithm based on word pairs / single words multiple repetition ratio.PloS one · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The advent of the digital era provided a fertile ground for the development of virtual societies, complex systems influencing real-world dynamics. Understanding online human behavior and its relevance beyond the digital boundaries is still an open challenge. Here we show that online social interactions during a massive voting event can be used to build an accurate map of real-world political parties and electoral ranks for Italian elections in 2018. We provide evidence that information flow and collective attention are often driven by a special class of highly influential users, that we name "augmented humans", who exploit thousands of automated agents, also known as bots, for enhancing their online influence. We show that augmented humans generate deep information cascades, to the same extent of news media and other broadcasters, while they uniformly infiltrate across the full range of identified groups. Digital augmentation represents the cyber-physical counterpart of the human desire to acquire power within social systems.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.