Publications by Carlos Castillo

SciClops: Detecting and Contextualizing Scientific Claims for Assisting Manual Fact-Checking

Karl Aberer, Panagiotis Smeros, Carlos Castillo

This paper describes SciClops, a method to help combat online scientific misinformation. Although automated fact-checking methods have gained significant attention recently, they require pre-existing ground-truth evidence, which, in the scientific context, ...

ACM2021

SciLens News Platform: A System for Real-Time Evaluation of News Articles

Karl Aberer, Angeliki Romanou, Panagiotis Smeros, Carlos Castillo

We demonstrate the SciLens News Platform, a novel system for evaluating the quality of news articles. The SciLens News Platform automatically collects contextual information about news articles in real-time and provides quality indicators about their valid ...

ASSOC COMPUTING MACHINERY2020

SciLens: Evaluating the Quality of Scientific News Articles Using Social Media and Scientific Literature Indicators

Karl Aberer, Panagiotis Smeros, Carlos Castillo

This paper describes, develops, and validates SciLens, a method to evaluate the quality of scientific news articles. The starting point for our work are structured methodologies that define a series of quality aspects for manually evaluating news. Based on ...

ASSOC COMPUTING MACHINERY2019

Predicting the Success of Online Petitions Leveraging Multidimensional Time-Series

Karl Aberer, Philippe Cudré-Mauroux, Julia Proskurnia, Carlos Castillo

Applying classical time-series analysis techniques to online content is challenging, as web data tends to have data quality issues and is often incomplete, noisy, or poorly aligned. In this paper, we tackle the problem of predicting the evolution of a time ...

Efficient Document Filtering Using Vector Space Topic Expansion and Pattern-Mining: The Case of Event Detection in Microposts

Karl Aberer, Philippe Cudré-Mauroux, Julia Proskurnia, Carlos Castillo

Automatically extracting information from social media is challenging given that social content is often noisy, ambiguous, and inconsistent. However, as many stories break on social channels first before being picked up by mainstream media, developing meth ...

2017

Combining Human Computing and Machine Learning to Make Sense of Big (Aerial) Data for Disaster Response

Stéphane Joost, Devis Tuia, Matthew Josef Parkan, Carlos Castillo, Muhammad Imran, Patrick Meier, Julien Briant

Aerial imagery captured via unmanned aerial vehicles (UAVs) is playing an increasingly important role in disaster response. Unlike satellite imagery, aerial imagery can be captured and processed within hours rather than days. In addition, the spatial resol ...

Mary Ann Liebert, Inc2016

Comparing Events Coverage in Online News and Social Media: The Case of Climate Change

Karl Aberer, Alexandra Olteanu, Carlos Castillo

Social media is becoming more and more integrated in the distribution and consumption of news. How is news in social media different from mainstream news? % This paper presents a comparative analysis covering a span of 17 months and hundreds of news events ...

2015

What to Expect When the Unexpected Happens: Social Media Communications Across Crises

Alexandra Olteanu, Carlos Castillo

2015

CrisisLex: A Lexicon for Collecting and Filtering Microblogged Communications in Crises

Alexandra Olteanu, Carlos Castillo

2014