Contents | Science 343, 6176
Publications | Network Science Institute at Northeastern University
A Google–Wikipedia–Twitter Model as a Leading Indicator of the Numbers of Coronavirus Deaths - O'Leary - 2020 - Intelligent Systems in Accounting, Finance and Management - Wiley Online Library
Frontiers | A survey of data element perspective: Application of artificial intelligence in health big data
Age-Related Differences in the Accuracy of Web Query-Based Predictions of Influenza-Like Illness | PLOS ONE
Statistical Analysis of Glycosylation Reactions - Chang - 2021 - Chemistry – A European Journal - Wiley Online Library
IJERPH | Free Full-Text | Toward Value-Based Healthcare through Interactive Process Mining in Emergency Rooms: The Stroke Case
The Parable of Google Flu: Traps in Big Data Analysis Share Your Story
Informatics: Make sense of health data | Nature
The Parable of Google Flu: Traps in Big Data Analysis | GARY KING
Google Flu Trends Still Appears Sick: An Evaluation of the 2013‐2014 Flu Season | GARY KING
Collective Attention and Stock Prices: Evidence from Google Trends Data on Standard and Poor's 100 | PLOS ONE
![Does Twitter language reliably predict heart disease? A commentary on Eichstaedt et al. (2015a) [PeerJ]](https://dfzljdn9uc3pi.cloudfront.net/2018/5656/1/fig-2-full.png "Does Twitter language reliably predict heart disease? A commentary on Eichstaedt et al. (2015a) [PeerJ]")
Does Twitter language reliably predict heart disease? A commentary on Eichstaedt et al. (2015a) [PeerJ]
Social media for large studies of behavior | Science
IJERPH | Free Full-Text | Infectious or Recovered? Optimizing the Infectious Disease Detection Process for Epidemic Control and Prevention Based on Social Media
Tackling misinformation: What researchers could do with social media data | HKS Misinformation Review
Faster indicators of chikungunya incidence using Google searches | PLOS Neglected Tropical Diseases
An early warning approach to monitor COVID-19 activity with multiple digital traces in near real time | Science Advances
Publications - NULab for Texts, Maps, and Networks
The Parable of Google Flu: Traps in Big Data Analysis
Alessandro Vespignani – MIDAS
A Novel Intelligent Hybrid Optimized Analytics and Streaming Engine for Medical Big Data
An early warning approach to monitor COVID-19 activity with multiple digital traces in near real time | Science Advances
Meaningful measures of human society in the twenty-first century | Nature
From Machine Learning to Artificial Intelligence Applications in Cardiac Care | Circulation
