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Found 8 papers, 0 papers with code
Language-Agnostic Modeling of Source Reliability on Wikipedia
For mid-resource languages, we achieve 0. 65 while the performance of low-resource languages varies; in all cases, the time the domain remains present in the articles (which we dub as permanence) is one of the most predictive features.
Quantitative Information Extraction from Humanitarian Documents
In this work, we contribute an annotated dataset for the humanitarian domain for the extraction of such quantitative information, along side its important context, including units it refers to, any modifiers, and the relevant event.
Leave no Place Behind: Improved Geolocation in Humanitarian Documents
Geographical location is a crucial element of humanitarian response, outlining vulnerable populations, ongoing events, and available resources.
Comfort Foods and Community Connectedness: Investigating Diet Change during COVID-19 Using YouTube Videos on Twitter
Unprecedented lockdowns at the start of the COVID-19 pandemic have drastically changed the routines of millions of people, potentially impacting important health-related behaviors.
Googling for Abortion: Search Engine Mediation of Abortion Accessibility in the United States
In this study we ask, to what degree does Google Search provide quality responses to users searching for an abortion provider, specifically in terms of directing them to abortion clinics (ACs) or CPCs.
Developing Annotated Resources for Internal Displacement Monitoring
This paper describes in details the design and development of a novel annotation framework and of annotated resources for Internal Displacement, as the outcome of a collaboration with the Internal Displacement Monitoring Centre, aimed at improving the accuracy of their monitoring platform IDETECT.
Kissing Cuisines: Exploring Worldwide Culinary Habits on the Web
In this paper, we present a large-scale study of recipes published on the web and their content, aiming to understand cuisines and culinary habits around the world.
Controversy and Sentiment in Online News
We find that in general, when it comes to controversial issues, the use of negative affect and biased language is prevalent, while the use of strong emotion is tempered.
