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BotOrNot: A System to Evaluate Social Bots
- Clayton A. Davis, Onur Varol, Emilio Ferrara, A. Flammini, F. Menczer
- Computer ScienceThe Web Conference
- 2 February 2016
BotOrNot, a publicly-available service that leverages more than one thousand features to evaluate the extent to which a Twitter account exhibits similarity to the known characteristics of social bots, is presented.
Online Human-Bot Interactions: Detection, Estimation, and Characterization
- Onur Varol, Emilio Ferrara, Clayton A. Davis, F. Menczer, A. Flammini
- Computer ScienceInternational Conference on Web and Social Media
- 9 March 2017
This work presents a framework to detect social bots on Twitter, and describes several subclasses of accounts, including spammers, self promoters, and accounts that post content from connected applications.
The rise of social bots
- Emilio Ferrara, Onur Varol, Clayton A. Davis, F. Menczer, A. Flammini
- EconomicsCommunications of the ACM
- 19 July 2014
Today's social bots are sophisticated and sometimes menacing. Indeed, their presence can endanger online ecosystems as well as our society.
Social Bots Distort the 2016 US Presidential Election Online Discussion
The findings suggest that the presence of social media bots can indeed negatively affect democratic political discussion rather than improving it, which in turn can potentially alter public opinion and endanger the integrity of the Presidential election.
Graph Embedding Techniques, Applications, and Performance: A Survey
Tracking Social Media Discourse About the COVID-19 Pandemic: Development of a Public Coronavirus Twitter Data Set
- Emily Chen, Kristina Lerman, Emilio Ferrara
- Computer ScienceJMIR Public Health and Surveillance
- 16 March 2020
Basic statistics that show that Twitter activity responds and reacts to COVID-19-related events are presented, to enable the study of online conversation dynamics in the context of a planetary-scale epidemic outbreak of unprecedented proportions and implications.
Defining and identifying Sleeping Beauties in science
- Qing Ke, Emilio Ferrara, F. Radicchi, A. Flammini
- Computer ScienceProceedings of the National Academy of Sciences
- 24 May 2015
A systematic, large-scale, and multidisciplinary analysis of the Sleeping Beauty phenomenon in science, introducing a parameter-free measure that quantifies the extent to which a specific paper can be considered an SB and revealing that the SB phenomenon is not exceptional.
Disinformation and Social Bot Operations in the Run Up to the 2017 French Presidential Election
- Emilio Ferrara
- Computer ScienceFirst Monday
- 30 June 2017
Anomalous account usage patterns suggest the possible existence of a black market for reusable political disinformation bots and a characterization of both the bots and the users who engaged with them, and oppose it to those users who didn’t.
Deep Neural Networks for Bot Detection
ReCOVery: A Multimodal Repository for COVID-19 News Credibility Research
- Xinyi Zhou, Apurva Mulay, Emilio Ferrara, R. Zafarani
- Computer ScienceInternational Conference on Information and…
- 9 June 2020
ReCOVery, a repository designed and constructed to facilitate research on combating information with low credibility regarding COVID-19, provides multimodal information of news articles on coronavirus, including textual, visual, temporal, and network information.