Leveraging Bias in Forensic Science

Dr. Simon Cole calls for a more hierarchical organization of forensic science in his challenging Article, Acculturating Forensic Science: What is ‘Scientific Culture’, and How can Forensic Science Adopt it? Koppl thinks Dr. Cole is right to say that there are different roles in forensic science, but somewhat mistaken in his call for hierarchy

Team QCRI-MIT at SemEval-2019 Task 4: Propaganda Analysis Meets Hyperpartisan News Detection

In this paper, we describe our submission to SemEval-2019 Task 4 on Hyperpartisan News Detection. Our system relies on a variety of engineered features originally used to detect propaganda. This is based on the assumption that biased messages are propagandistic in the sense that they promote a particular political cause or viewpoint. We trained a logistic regression model with features ranging from simple bag-of-words to vocabulary richness and text readability features. Our system achieved 72.9% accuracy on the test data that is annotated manually and 60.8% on the test data that is annotated with distant supervision. Additional experiments showed that significant performance improvements can be achieved with better feature pre-processing.Comment: Hyperpartisanship, propaganda, news media, fake news, SemEval-201

False News On Social Media: A Data-Driven Survey

In the past few years, the research community has dedicated growing interest to the issue of false news circulating on social networks. The widespread attention on detecting and characterizing false news has been motivated by considerable backlashes of this threat against the real world. As a matter of fact, social media platforms exhibit peculiar characteristics, with respect to traditional news outlets, which have been particularly favorable to the proliferation of deceptive information. They also present unique challenges for all kind of potential interventions on the subject. As this issue becomes of global concern, it is also gaining more attention in academia. The aim of this survey is to offer a comprehensive study on the recent advances in terms of detection, characterization and mitigation of false news that propagate on social media, as well as the challenges and the open questions that await future research on the field. We use a data-driven approach, focusing on a classification of the features that are used in each study to characterize false information and on the datasets used for instructing classification methods. At the end of the survey, we highlight emerging approaches that look most promising for addressing false news

Unmasking the Teen Cyberbully: A First Amendment-Compliant Approach to Protecting Child Victims of Anonymous, School-Related Internet Harassment

In proposing a new rule under the First Amendment to adjudicate anonymous Cyberbullying cases, this Article first reviews and summarizes the First Amendment precedents governing regulation of speech by minors and student speech in the school environment. Second, it reviews and discusses the prevalence of minors’ online harassment or Cyberbullying, including pre-litigation disputes reported in the press. Third, it reviews and summarizes the First Amendment precedents governing the “unmasking” of anonymous speakers. Finally, the Cyberbully Unmasking Test is proposed and applied

The Costs and Benefits of Forensics

Supreme Court Justice Louis Brandeis famously wrote that states can be laboratories for experimentation in law and policy. Disappointingly, however, the actual laboratories that states and local governments run are not a home for experimentation. We do not have adequate information about either the costs or the benefits of forensic testing or allocation of resources. Increased spending and expansion of crime laboratories has perversely accompanied growing backlogs. Poor quality control has resulted in a series of audits and even closures of crime laboratories. In response to these problems, however, some laboratories and some entire states have developed new approaches toward oversight. In this Article, I will describe the growth of crime labs and the resources dedicated to them, but also the backlogs that have resulted from far too much in the way of quantity. Second, I will discuss the problem of resource allocation in forensics, including the differing perspectives and interests of police and forensic agencies that should both be taken into account. Third, I will describe quality control challenges that have accompanied the explosion in the use of forensics. Fourth, I will describe how regulation could better address both resource allocation and quality control, as well as how the Houston Forensic Science Center has become a model for regulating both the quality and the quantity of forensics. Finally, I will ask why the federal government has not done more to help improve the quality of forensics even as it has helped to encourage overwhelming and unnecessary quantity

Analyzing the Digital Traces of Political Manipulation: The 2016 Russian Interference Twitter Campaign

Until recently, social media was seen to promote democratic discourse on social and political issues. However, this powerful communication platform has come under scrutiny for allowing hostile actors to exploit online discussions in an attempt to manipulate public opinion. A case in point is the ongoing U.S. Congress' investigation of Russian interference in the 2016 U.S. election campaign, with Russia accused of using trolls (malicious accounts created to manipulate) and bots to spread misinformation and politically biased information. In this study, we explore the effects of this manipulation campaign, taking a closer look at users who re-shared the posts produced on Twitter by the Russian troll accounts publicly disclosed by U.S. Congress investigation. We collected a dataset with over 43 million election-related posts shared on Twitter between September 16 and October 21, 2016, by about 5.7 million distinct users. This dataset included accounts associated with the identified Russian trolls. We use label propagation to infer the ideology of all users based on the news sources they shared. This method enables us to classify a large number of users as liberal or conservative with precision and recall above 90%. Conservatives retweeted Russian trolls about 31 times more often than liberals and produced 36x more tweets. Additionally, most retweets of troll content originated from two Southern states: Tennessee and Texas. Using state-of-the-art bot detection techniques, we estimated that about 4.9% and 6.2% of liberal and conservative users respectively were bots. Text analysis on the content shared by trolls reveals that they had a mostly conservative, pro-Trump agenda. Although an ideologically broad swath of Twitter users was exposed to Russian Trolls in the period leading up to the 2016 U.S. Presidential election, it was mainly conservatives who helped amplify their message

How Latino Anti-Blackness Upholds Racism In The United States: A Counterstory Book Review Of Tanya Katerí Hernández’s Racial Innocence

In this piece, the author uses counterstorytelling as a research method to write a book review of Tanya Katerí Hernández’s recently published book, Racial Innocence: Unmasking Latino Anti-Black Bias and the Struggle for Equality. Specifically, in this counterstory, the author created two composite characters, Alberto and his mother, Lola, made up of arguments from the book to engage in a real and critical dialogue about the anti-Blackness amongst Latinos in the United States. Drawing on Hernández’s argument that Latino anti-Blackness upholds racism, the author uses this counterstory to illustrate the various ways Latinos enact anti-Black ideologies and practices to deny Black people good experiences in public spaces, a quality education, work opportunities, housing, and physical and psychological safety. The author argues that counterstorytelling allows him to make research accessible — digestible and understandable — to his community and other Communities of Color who continue to be systematically excluded from academia and knowledge production in higher education

Choosing COVID-19 treatment over prevention through vaccination: A U.S. social media case study

Background: This study examined anti-vaccination social media posts that favored COVID-19 treatment (monoclonal antibodies (mAbs)) rather than prevention through vaccination, both of which were under Emergency Use Authorization rather than full approval from the U.S. Food and Drug Administration at the time of this study. Our research stemmed from participation in a U.S. public health education campaign led by a coalition of government agencies to expand provider and health system use of mAbs with high-risk COVID-19 positive patients. Aim: Inform real world communication strategies for treatment over prevention therapies. Methods: We analyzed the most-engaged tweets that mentioned mAbs and vaccines from March 1 to August 31, 2021. Results: Our qualitative analysis identified the following themes: distrust in science, individualism, and politically oriented or partisan sentiment. Discussion: Countering anti-vaccine messages and reducing the susceptibility of vaccine-hesitant individuals to these messages must involve message design that considers the individualism and distrust revealed in this study. We recommend two approaches: (1) unmasking anti-vaccine messaging techniques; (2) using colloquial and values-driven language. Conclusions: Our findings reinforce the need for public health practitioners to monitor public and social media discourse, adopt messaging that navigates anti-vaccine sentiment, and engage with the preference for treatment over prevention