http://ncri.io/projects/
Acting as a neutral, “White Label” the NCRI seeks to innovate exacting internal standards of objectivity, data security, and strict legal compliance. It seeks to earn the trust of the public and social networks and merit the trust it earns in order to afford transparency.
Activities
We collect billions of posts from fringe and mainstream websites and millions of images which we analyze with artificial intelligence.
We issue peer-reviewed reports and data-journalism on our blog that detail our findings to the public to help us better understand and hopefully treat the ominous infection of hate in modern political life.
To catalyze greater transparency and self reflection in social networks in order to mitigate the epidemic of hate and deceit.
The NCRI seeks to act as a conscience on social networks — We aim to be whistle blowers, to bring public attention and civil discourse to ominous trends in network hate.
https://arxiv.org/abs/1805.12512
On the Origins of Memes by Means of Fringe Web Communities
Internet memes are increasingly used to sway and manipulate public opinion. This prompts the need to study their propagation, evolution, and influence across the Web. In this paper, we detect and measure the propagation of memes across multiple Web communities, using a processing pipeline based on perceptual hashing and clustering techniques, and a dataset of 160M images from 2.6B posts gathered from Twitter, Reddit, 4chan's Politically Incorrect board (/pol/), and Gab, over the course of 13 months. We group the images posted on fringe Web communities (/pol/, Gab, and The_Donald subreddit) into clusters, annotate them using meme metadata obtained from Know Your Meme, and also map images from mainstream communities (Twitter and Reddit) to the clusters.
Our analysis provides an assessment of the popularity and diversity of memes in the context of each community, showing, e.g., that racist memes are extremely common in fringe Web communities. We also find a substantial number of politics-related memes on both mainstream and fringe Web communities, supporting media reports that memes might be used to enhance or harm politicians. Finally, we use Hawkes processes to model the interplay between Web communities and quantify their reciprocal influence, finding that /pol/ substantially influences the meme ecosystem with the number of memes it produces, while \td has a higher success rate in pushing them to other communities.