About The NELA Toolkit

What is The NELA Toolkit?

The News Landscape (NELA) Toolkit is an open source toolkit for the systematic exploration of the news landscape. The goal of NELA is to both speed up human fact-checking efforts and increase the understanding of online news as a whole. NELA is made up of multiple indepedent modules, that work at article level granularity: reliability prediction, political impartiality prediction, text objectivity prediction, and reddit community interest prediction. As well as, modules that work at source level granularity: reliability prediction, political impartiality prediction, content-based feature visualization.


How does it work?

NELA is built using a mix of machine learning techniques on well-studied natural language features. Details can be found in our WWW 2018 paper!


Can I use the NELA data set for research?

Yes! You can request any of our data sets here.


Does the NELA Toolkit have an API?

The NELA Toolkit currently does not have an API, but it is in the works.


Who made The NELA Toolkit?

The NELA Toolkit is based on information credibility research by Benjamin Horne and Sibel Adalı, and is built with the help of William Dron and Sara Khedr.

Benjamin Horne is a PhD student in Computer Science at Rensselaer Polytechnic Institute. His research focuses on online information quality and credibility, along with the human decisions in assessing online information. This work utilizes techniques in machine learning, natural language processing, and social network analysis to both characterize and detect the veracity information, in hopes of not only building better tools for decision making, but in understanding how the human impacts those decisions. To learn more about his work, check out his website.

William Dron is a Senior Scientist at Raytheon BBN Technologies, where he has worked since 2004. William has a background in communications networks and computer science, particularly for military use. Over the past 8 years, he has focused on cross network genre experimentation and has incorporated social and information sciences in his work. He is particularly interested in utilizing software engineering principles and visualizations to create cohesive and scalable software solutions.

Sara Khedr is a Master’s student in the Computer Science department at Rensselaer Polytechnic Institute (RPI). She received her Bachelor’s degree in Computer and System Engineering from RPI. During her education, Sara has focused on attaining general software development experience and has previously interned for Workday and Salesforce, two SaaS companies.

Dr. Sibel Adalı is a Professor and Associate Head of Computer Science at Renssealer Polytechnic Institute. Her research concentrates on cross-cutting problems related to trust, information processing, and social networks. As part of her work, she has worked as the ARL-lead Network Science Collaborative Technology Alliance (NS-CTA) wide Trust Coordinator, Social and Cognitive Networks Academic Research Center (SCNARC) Associate Director. She serves as associate editor for ACM Transactions on Internet Technology. She is the author of a book on Modeling Trust Context in Networks, released in 2013 by Springer. For more on her work, check out her website.

Research was sponsored by the Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-09-2-0053 (the ARL Network Science CTA). The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on.

Where can I see related work?

Here are several papers on the research behind NELA:

Benjamin D. Horne, William Dron, Sara Khedr, and Sibel Adali. "Assessing the News Landscape: A Multi-Module Toolkit for Evaluating the Credibility of News" WWW 2018

Benjamin D. Horne, Sara Khedr, and Sibel Adali. "Sampling the News Producers: A Large News and Feature Data Set for the Study of the Complex Media Landscape" ICWSM 2018

Horne, Benjamin D., and Sibel Adali. "This Just In: Fake News Packs a Lot in Title, Uses Simpler, Repetitive Content in Text Body, More Similar to Satire than Real News." NECO Workshop 2017

Horne, Benjamin D., Sibel Adali, and Sujoy Sikdar. "Identifying the social signals that drive online discussions: A case study of Reddit communities." ICCCN 2017