• Publications
  • Influence
BotOrNot: A System to Evaluate Social Bots
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. Expand
The rise of social bots
Today's social bots are sophisticated and sometimes menacing. Indeed, their presence can endanger online ecosystems as well as our society.
Online Human-Bot Interactions: Detection, Estimation, and Characterization
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. Expand
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. Expand
Graph Embedding Techniques, Applications, and Performance: A Survey
A comprehensive and structured analysis of various graph embedding techniques proposed in the literature, and the open-source Python library, named GEM (Graph Embedding Methods, available at https://github.com/palash1992/GEM ), which provides all presented algorithms within a unified interface to foster and facilitate research on the topic. Expand
Defining and identifying Sleeping Beauties in science
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. Expand
Disinformation and social bot operations in the run up to the 2017 French presidential election
  • Emilio Ferrara
  • Political Science, Computer Science
  • First Monday
  • 1 July 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. Expand
Tracking Social Media Discourse About the COVID-19 Pandemic: Development of a Public Coronavirus Twitter Data Set
Background At the time of this writing, the coronavirus disease (COVID-19) pandemic outbreak has already put tremendous strain on many countries' citizens, resources, and economies around the world.Expand
Deep Neural Networks for Bot Detection
This paper proposes a deep neural network based on contextual long short-term memory (LSTM) architecture that exploits both content and metadata to detect bots at the tweet level, and applies the same architecture to account-level bot detection, achieving nearly perfect classification accuracy. Expand
The DARPA Twitter Bot Challenge
There is a need to identify and eliminate "influence bots" - realistic, automated identities that illicitly shape discussions on sites like Twitter and Facebook - before they get too influential. Expand