Russian Twitter disinformation campaigns reach across the American political spectrum

Evidence from an analysis of Twitter data reveals that Russian social media trolls exploited racial and political identities to infiltrate distinct groups of authentic users, playing on their group identities. The groups affected spanned the ideological spectrum, suggesting the importance of coordinated counter-responses from diverse coalitions of users

The filter map: Media and the pursuit of truth and legitimacy

What kinds of media messages should we choose to receive, and how seriously should we take them? These questions are much more urgent now than they were in the pre-digital era, when we had far less control over the information we consumed. Back then, nearly all our media options came from the major TV networks, movie studios, book publishers, radio broadcasters and local news monopolies. Today, anyone can add to our inexhaustible menu of media choices, which continue to expand without pause. With so many choices at our fingertips, filtering becomes a top priority to arrive at any coherent understanding of the world beyond our direct experience. But what principles ought to drive our filtering and interpretive criteria? The standard answer to this question starts from the assumption that many of us don’t always make the best choices about what information to consume. As with food, what appeals to us most immediately is not always the healthiest or most useful — for example, soft news and infotainment are sometimes blamed for emphasizing the most salacious and least consequential aspects of public affairs. But even worse is factually untrue content designed to look authentic (what is sometimes called “fake news”), which usually targets those who agree with the false message. Extreme opinions can be equally harmful, as when they advocate for the systematic injury, oppression, or extermination of entire ethnicities, sexual orientations, or religious groups. I argue that, generally, people are well justified in avoiding such content

Beyond the hashtags: #Ferguson, #Blacklivesmatter, and the online struggle for offline justice

In 2014, a dedicated activist movement--Black Lives Matter (BLM)--ignited an urgent national conversation about police killings of unarmed Black citizens. Online tools have been anecdotally credited as critical in this effort, but researchers are only beginning to evaluate this claim. This research report examines the movement's uses of online media in 2014 and 2015. To do so, we analyze three types of data: 40.8 million tweets, over 100,000 web links, and 40 interviews of BLM activists and allies

How Black Twitter and Other Social Media Communities Interact With Mainstream News

People have been forming communities using digital communication technologies since long before the web as we know it today. Social media are only the latest in a long series of digital forums that have enabled global conversations and connections around nearly any topic imaginable. With its emphasis on public accessibility and real-time content production, Twitter has become a major hub for communities of all types and sizes. The issues and voices of people of color and women have attracted much attention from professional journalists over the past few years.1 Yet many such individuals have criticized journalists’ portrayals and coverage of issues that are important to them. In response, some participants have assumed the role of news creators and distributors, focusing on their communities’ particular concerns.2 Understanding these emerging social subcultures will allow more accurate portrayals of diverse communities and yield insights for better journalistic engagement in the digital age

Black trolls matter : Racial and ideological asymmetries in social media disinformation

The recent rise of disinformation and propaganda on social media has attracted strong interest from social scientists. Research on the topic has repeatedly observed ideological asymmetries in disinformation content and reception, wherein conservatives are more likely to view, redistribute, and believe such content. However, preliminary evidence has suggested that race may also play a substantial role in determining the targeting and consumption of disinformation content. Such racial asymmetries may exist alongside, or even instead of, ideological ones. Our computational analysis of 5.2 million tweets by the Russian government-funded “troll farm” known as the Internet Research Agency sheds light on these possibilities. We find stark differences in the numbers of unique accounts and tweets originating from ostensibly liberal, conservative, and Black left-leaning individuals. But diverging from prior empirical accounts, we find racial presentation—specifically, presenting as a Black activist—to be the most effective predictor of disinformation engagement by far. Importantly, these results could only be detected once we disaggregated Black-presenting accounts from non-Black liberal accounts. In addition to its contributions to the study of ideological asymmetry in disinformation content and reception, this study also underscores the general relevance of race to disinformation studies

Opening Closed Regimes: What was the Role of Social Media during the Arab Spring?

Social media played a central role in shaping political debates in the Arab Spring. A spike in online revolutionary conversations often preceded major events on the ground. Social media helped spread democratic ideas across international borders.National Science Foundationhttp://deepblue.lib.umich.edu/bitstream/2027.42/117568/1/2011_Howard-Duffy-Freelon-Hussain-Mari-Mazaid_PITPI.pd

Digital Trace Data Collection for Social Media Effects Research: APIs, Data Donation, and (Screen) Tracking

In social media effects research, the role of specific social media content is understudied, in part attributable to the fact that communication science previously lacked methods to access social media content directly. Digital trace data (DTD) can shed light on textual and audio-visual content of social media use and enable the analysis of content usage on a granular individual level that has been previously unavailable. However, because digital trace data are not specifically designed for research purposes, collection and analysis present several uncertainties. This article is a collaborative effort by scholars to provide an overview of how three methods of digital trace data collection - APIs, data donations, and tracking - can be used in studying the effects of social media content in three important topic areas of communication research: misinformation, algorithmic bias, and well-being. We address the question of how to collect raw social media content data and arrive at meaningful measures with multiple state-of-the-art data collection techniques that can be used to study the effects of social media use on different levels of detail. We conclude with a discussion of best practices for the implementation of each technique, and a comparison of their advantages and disadvantages

Digital Trace Data Collection for Social Media Effects Research: APIs, Data Donation, and (Screen) Tracking

In social media effects research, the role of specific social media content is understudied, in part attributable to the fact that communication science previously lacked methods to access social media content directly. Digital trace data (DTD) can shed light on textual and audio-visual content of social media use and enable the analysis of content usage on a granular individual level that has been previously unavailable. However, because digital trace data are not specifically designed for research purposes, collection and analysis present several uncertainties. This article is a collaborative effort by scholars to provide an overview of how three methods of digital trace data collection - APIs, data donations, and tracking - can be used in studying the effects of social media content in three important topic areas of communication research: misinformation, algorithmic bias, and well-being. We address the question of how to collect raw social media content data and arrive at meaningful measures with multiple state-of-the-art data collection techniques that can be used to study the effects of social media use on different levels of detail. We conclude with a discussion of best practices for the implementation of each technique, and a comparison of their advantages and disadvantages

The Filter Map: Media and the Pursuit of Truth and Legitimacy

Filter bubbles are only part of the problem. This piece argues that we need to think about truth, legitimacy, and agreeableness when consuming news, and introduces a three-dimensional filter map to help structure our media selection criteria

Code and data for "What’s in your PIE? Understanding the contents of personalized information environments with PIEGraph"

Code and data for "What’s in your PIE? Understanding the contents of personalized information environments with PIEGraph," forthcoming in JASIS