The Fake News Spreading Plague: Was it Preventable?

In 2010, a paper entitled "From Obscurity to Prominence in Minutes: Political Speech and Real-time search" won the Best Paper Prize of the Web Science 2010 Conference. Among its findings were the discovery and documentation of what was termed a "Twitter-bomb", an organized effort to spread misinformation about the democratic candidate Martha Coakley through anonymous Twitter accounts. In this paper, after summarizing the details of that event, we outline the recipe of how social networks are used to spread misinformation. One of the most important steps in such a recipe is the "infiltration" of a community of users who are already engaged in conversations about a topic, to use them as organic spreaders of misinformation in their extended subnetworks. Then, we take this misinformation spreading recipe and indicate how it was successfully used to spread fake news during the 2016 U.S. Presidential Election. The main differences between the scenarios are the use of Facebook instead of Twitter, and the respective motivations (in 2010: political influence; in 2016: financial benefit through online advertising). After situating these events in the broader context of exploiting the Web, we seize this opportunity to address limitations of the reach of research findings and to start a conversation about how communities of researchers can increase their impact on real-world societal issues

System and Method for Parallel Error Diffusion Dithering

A system is disclosed for error diffusion dithering. The system includes an input for receiving an input matrix representative of image data, and a plurality of processors. The plurality of processors processes the input matrix and provides output data. Each of the processors is in communication with at least a portion of the input matrix. At least one processor processes a portion of the input matrix defined at least in part by a substantially diagonal edge within the image matrix

Investigating Rumor Propagation with TwitterTrails

Social media have become part of modern news reporting, used by journalists to spread information and find sources, or as a news source by individuals. The quest for prominence and recognition on social media sites like Twitter can sometimes eclipse accuracy and lead to the spread of false information. As a way to study and react to this trend, we introduce {\sc TwitterTrails}, an interactive, web-based tool ({\tt twittertrails.com}) that allows users to investigate the origin and propagation characteristics of a rumor and its refutation, if any, on Twitter. Visualizations of burst activity, propagation timeline, retweet and co-retweeted networks help its users trace the spread of a story. Within minutes {\sc TwitterTrails} will collect relevant tweets and automatically answer several important questions regarding a rumor: its originator, burst characteristics, propagators and main actors according to the audience. In addition, it will compute and report the rumor's level of visibility and, as an example of the power of crowdsourcing, the audience's skepticism towards it which correlates with the rumor's credibility. We envision {\sc TwitterTrails} as valuable tool for individual use, but we especially for amateur and professional journalists investigating recent and breaking stories. Further, its expanding collection of investigated rumors can be used to answer questions regarding the amount and success of misinformation on Twitter.Comment: 10 pages, 8 figures, under revie

DEMO: Using TwitterTrails.com to Investigate Rumor Propagation

Social media have become part of modern news reporting, used by journalists to spread information and find sources, or as a news source by individuals. The quest for prominence and recognition on social media sites like Twitter can sometimes eclipse accuracy and lead to the spread of false information. As a way to study and react to this trend, we demo TWITTERTRAILS, an interactive, webbased tool (twittertrails.com) that allows users to investigate the origin and propagation characteristics of a rumor and its refutation, if any, on Twitter. Visualizations of burst activity, propagation timeline, retweet and co-retweeted networks help its users trace the spread of a story. Within minutes TWITTERTRAILS will collect relevant tweets and automatically answer several important questions regarding a rumor: its originator, burst characteristics, propagators and main actors according to the audience. In addition, it will compute and report the rumor’s level of visibility and, as an example of the power of crowdsourcing, the audience’s skepticism towards it which correlates with the rumor’s credibility. We envision TWITTERTRAILS as valuable tool for individual use, and especially for amateur and professional journalists investigating recent and breaking stories

Information Systems for “Wicked Problems” - Research at the Intersection of Social Media and Collective Intelligence

The objective of this commentary is to propose fruitful research directions built upon the reciprocal interplay of social media and collective intelligence. We focus on “wicked problems” – a class of problems that Introne et al. (Künstl. Intell. 27:45–52, 2013) call “prob- lems for which no single computational formulation of the problem is suffi- cient, for which different stakeholders do not even agree on what the prob- lem really is, and for which there are no right or wrong answers, only answers that are better or worse from differ- ent points of view”. We argue that in- formation systems research in partic- ular can aid in designing appropriate systems due to benefits derived from the combined perspectives of both so- cial media and collective intelligence. We document the relevance and time- liness of social media and collective in- telligence for business and information systems engineering, pinpoint needed functionality of information systems for wicked problems, describe related re- search challenges, highlight prospec- tive suitable methods to tackle those challenges, and review examples of initial results