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

Classroom Management and Remote Teaching: Tools for Defining and Teaching Expectations

The remote instruction context presents many challenges for teachers, including managing student behavior. The practice of defining and teaching expectations is considered a high-leverage practice in special education, and should be applied to the remote setting to support the learning of students with and without disabilities. We present four recommended steps for adapting this practice for the remote setting and use a fictional vignette with example materials to demonstrate the process. Additionally, we provide other useful online resources for providing effective online instruction for students with disabilities

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

Properties of the KISS Green Pea Galaxies

Green peas (GPs) are a class of extreme star-forming galaxies (SFGs) at intermediate redshifts, originally discovered via color selection using multifilter, wide-field survey imaging data. They are commonly thought of as being analogs of high-redshift Lyα-emitting galaxies. The defining characteristic of GP galaxies is a high-excitation nebular spectrum with very large equivalent width lines, leading to the recognition that GP-like galaxies can also be identified in samples of emission-line galaxies. Here we compare the properties a sample of [O iii]-selected SFGs (z = 0.29–0.41) from the KPNO International Spectroscopic Survey (KISS) with the color-selected GPs. We find that the KISS [O iii]-selected galaxies overlap with the parameter space defined by the color-selected GPs; the two samples appear to be drawn from the same population of objects. We compare the KISS GPs with the full Hα-selected KISS SFG sample (z < 0.1) and find that they are extreme systems. Many appear to be young systems at their observed look-back times (3–4 Gyr), with more than 90% of their rest-frame B-band luminosity coming from the starburst population. We compute the volume density of the KISS red (KISSR) GPs at z = 0.29–0.41 and find that they are extremely rare objects. We do not see galaxies as extreme as the KISSR GPs in the local universe, although we recognize several lower-luminosity systems at z < 0.1

Properties of the KISS Green Pea Galaxies

Green Peas are a class of extreme star-forming galaxies at intermediate redshifts, originally discovered via color-selection using multi-filter, wide-field survey imaging data (Cardamone et al. 2009). They are commonly thought of as being analogs of high-redshift Ly$\alpha$-emitting galaxies. The defining characteristic of Green Pea galaxies is a high-excitation nebular spectrum with very large equivalent width lines, leading to the recognition that Green Pea-like galaxies can also be identified in samples of emission-line galaxies. Here we compare the properties a sample of [O III]-selected star-forming galaxies (z = 0.29-0.41) from the KPNO International Spectroscopic Survey (KISS) with the color-selected Green Peas. We find that the KISS [O III]-selected galaxies overlap with the parameter space defined by the color-selected Green Peas; the two samples appear to be drawn from the same population of objects. We compare the KISS Green Peas with the full H$\alpha$-selected KISS star-forming galaxy sample (z $<$ 0.1) and find that they are extreme systems. Many appear to be young systems at their observed look-back times (3-4 Gyr), with more than 90% of their rest-frame B-band luminosity coming from the starburst population. We compute the volume density of the KISSR Green Peas at z = 0.29-0.41 and find that they are extremely rare objects. We don't see galaxies as extreme as the KISSR Green Peas in the local Universe, although we recognize several lower-luminosity systems at z $<$ 0.1.Comment: 21 pages, 12 figures. Accepted for publication in the Astrophysical Journa

Classroom Activity for Critical Analysis of News Propagation Online

We present an educational activity for college students to think critically about the truthfulness of news propagated in social media. This activity utilizes TwitterTrails, a visual tool to analyze Twitter claims, events, and memes. This tool provides views such as a propagation graph of a story’s bursting activity, and the co-ReTweeted network of the more prominent members of the audience. Using a response and reflection form, students are guided through these different facets of a story. The classroom activity was iteratively designed over the course of three semesters. Here, we present the learning outcomes from our final semester’s evaluation with 43 students. Our findings demonstrate that the activity provided students with both the conceptual tools and motivation to investigate the reliability of stories in social media. Our contribution also includes access to the tool and materials to conduct this activity. We hope that other educators will further improve and run this activity with their own students

From Personal Genomics to Twitter: Visualizing the Uncertainty of Evidence

Personal genomics offers a complex form of uncertainty in which a person’s data are largely stable, but the interpretation and implications continue to evolve with the emergence of new research. Another domain, in which there is uncertainty about the supporting evidence and truthfulness of a claim, is social networks. We propose that a similar method can be used to communicate uncertainty in these contexts, and present a tool for visualizing social network claims that builds upon research in both contexts