28 Result(s)
within
Alessandro Flammini
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Article
Open AccessA language framework for modeling social media account behavior
Malicious actors exploit social media to inflate stock prices, sway elections, spread misinformation, and sow discord. To these ends, they employ tactics that include the use of inauthentic accounts and campai...
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Article
Making food transport data matter
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Article
Open AccessCorrection to: Social influence and unfollowing accelerate the emergence of echo chambers
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Article
Open AccessOnline misinformation is linked to early COVID-19 vaccination hesitancy and refusal
Widespread uptake of vaccines is necessary to achieve herd immunity. However, uptake rates have varied across U.S. states during the first six months of the COVID-19 vaccination program. Misbeliefs may play an...
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Article
Political audience diversity and news reliability in algorithmic ranking
Newsfeed algorithms frequently amplify misinformation and other low-quality content. How can social media platforms more effectively promote reliable information? Existing approaches are difficult to scale and...
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Article
Open AccessUniversality, criticality and complexity of information propagation in social media
Statistical laws of information avalanches in social media appear, at least according to existing empirical studies, not robust across systems. As a consequence, radically different processes may represent pla...
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Article
Open AccessSocial influence and unfollowing accelerate the emergence of echo chambers
While social media make it easy to connect with and access information from anyone, they also facilitate basic influence and unfriending mechanisms that may lead to segregated and polarized clusters known as “...
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Article
Open AccessOn the challenges of predicting microscopic dynamics of online conversations
To what extent can we predict the structure of online conversation trees? We present a generative model to predict the size and evolution of threaded conversations on social media by combining machine learning...
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Article
Retraction Note: Limited individual attention and online virality of low-quality information
The authors wish to retract this Letter as follow-up work has highlighted that two errors were committed in the analyses used to produce Figs 4d and 5. In Fig. 4d, a software bug led to an incorrect value of t...
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Chapter and Conference Paper
Massive Multi-agent Data-Driven Simulations of the GitHub Ecosystem
Simulating and predicting planetary-scale techno-social systems pos...
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Article
Open AccessThe spread of low-credibility content by social bots
The massive spread of digital misinformation has been identified as a major threat to democracies. Communication, cognitive, social, and computer scientists are studying the complex causes for the viral diffus...
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Article
Open AccessHow algorithmic popularity bias hinders or promotes quality
Algorithms that favor popular items are used to help us select among many choices, from top-ranked search engine results to highly-cited scientific papers. The goal of these algorithms is to identify high-qual...
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Chapter
Optimal Modularity in Complex Contagion
In this chapter, we apply the theoretical framework introduced in the previous chapter to study how the modular structure of the social network affects the spreading of complex contagion. In particular, we foc...
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Chapter
Attention on Weak Ties in Social and Communication Networks
Granovetter’s weak tie theory of social networks is built around two central hypotheses. The first states that strong social ties carry the large majority of interaction events; the second maintains that weak ...
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Article
Open AccessEarly detection of promoted campaigns on social media
Social media expose millions of users every day to information campaigns - some emerging organically from grassroots activity, others sustained by advertising or other coordinated efforts. These campaigns cont...
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Article
Limited individual attention and online virality of low-quality information
Social media are massive marketplaces where ideas and news compete for our attention1. Previous studies have shown that quality is not a necessary condition for online virality2 and that knowledge about peer choi...
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Chapter and Conference Paper
Predicting Online Extremism, Content Adopters, and Interaction Reciprocity
We present a machine learning framework that leverages a mixture of metadata, network, and temporal features to detect extremist users, and predict content adopters and interaction reciprocity in social media....
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Article
Open AccessThe production of information in the attention economy
Online traces of human activity offer novel opportunities to study the dynamics of complex knowledge exchange networks, in particular how emergent patterns of collective attention determine what new informatio...
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Chapter
Online Interactions
The ubiquitous use of the Internet has led to the emergence of countless social media and social networking platforms, which generate large-scale digital data records of human behaviors online. Here we review ...
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Article
Open AccessCollective behaviors and networks
The goal of this thematic series is to provide a discussion venue about recent advances in the study of networks and their applications to the study of collective behavior in socio-technical systems. The serie...
