Welcome to the Era of Fake News

For the news industry, information is used to tell stories, which have traditionally been organized around “facts”. A growing problem, however, is that fact-based evidence is not relevant to a growing segment of the populace. Journalists need facts to tell stories, but they need data to understand how to engage audiences with this accurate information. The implementation of data is part of the solution to countering the erosion of trust and the decay of social discourse across networked spaces. Rather than following “trends”, news organizations should establish the groundwork to make facts “matter” by shaping the narrative instead of following deceptive statements.


Introduction
"Fake news. It's complicated", writes Claire Wardle (2017). While the term is problematic in application, it is useful for framing the larger structural issues in the media ecosystem. In modern news reporting, stories are traditionally organized around facts. Due in part to the plenitude of online sources, however, factual reporting can be displaced with "alternative" narratives. The use of the "fake news" label to denote organizational untrustworthiness is a related concern, as it portrays media watchdogs as entities that operate to deliberately misinform. The rising culture of institutional rejection in the United States and United Kingdom has resulted in a coup for fringe politics, encouraging xenophobia and hate speech (Anderson-Nathe & Gharabaghi, 2017).
Social interaction is at the heart of the "fake news" debate. To deconstruct the changing environment, highlighting the dual role of media as both sources of information and sites of coordination is vital, "because groups that see or hear or watch or listen to something can now gather around and talk to each other" (Shirky, 2009). Due to the disinhibitory effects of online inter-action, ideological echo chambers, and increasing tribalism (Rainie, Anderson, & Albright, 2017), the emotional component of sharing means news can be used to target and influence segments of the public. "If readers are the new publishers", writes Jason Tanz, "the best way to get them to share a story is by appealing to their feelings" (2017, p. 48).
As such, the study of the "fake news" ecosystem involves reconstructing how audiences express sentiment around news development. By tracing the flow of information across expansive networks of websites, profiles, and platforms, we can "gain insight into the mutual shaping of platforms and apps…as part of a larger online structure where every single tweak affects another part of the system" (Van Dijck, 2013, p. 285). With these structural considerations in mind, I outline a few considerations for media and communication research in the "fake news" era.

Transparency and Trust
First, proprietary "black box" (Pasquale, 2015) technologies, including opaque filtering, ranking, and recommen-dation algorithms, mediate access to information at the mass (e.g., group) and micro (e.g., individual) communication levels. In addition to the delivery of content, platform tools are built from the ground-up to establish the underlying context around users' interactions (e.g., Facebook's "like" button). Van Dijck explains: Social media are inevitably automated systems that engineer and manipulate connections. In order to be able to recognize what people want and like, Facebook and other platforms track desires by coding relationships between people, things, and ideas into algorithms. (2013, p. 12) Importantly, the provision of information through opaque technologies disrupts the layer of organizational credibility and reputational trust established in the process of professional reporting. This lack of transparency is also problematic in the sense that information literacy, defined as the ability to "recognize when information is needed and have the ability to locate, evaluate, and use [it]" (American Library Association, 2000) is less useful when the mechanisms used to "locate" and "evaluate" the information (e.g., topical search results) are not fully known.

Social Distortion
The mechanisms through which attention can be influenced is another consideration in the study of the broader "fake news" environment. For instance, thirdparty applications allow the rapid amplification of emotionally-charged messages across platforms such as Twitter. This strategic distortion of attention can hasten the spread of misinformation and the establishment of "alternative facts": When a Facebook user posts, the words they choose influence the words chosen later by their friends. This effect is consistent with prior research on emotional contagion, in that the friends of people who express emotional language end up expressing samevalence language. (Kramer, as cited in Turow & Tsui, 2008, p. 769) Sentiment-based sharing tools (e.g., Facebook's "reaction" emoji) further complicate the social distortion problem, as they codify and aggregate sentiment that is attached to news. This means that even if a controversial claim can be adequately "fact-checked", it may have already sowed outrage or confusion for its target audience.

Attention Models
A third challenge in the "fake news" era involves the industry model traditionally focused on the "manufacturing" of audiences (Bermejo, 2009). Through the collection of "detailed and intimate knowledge of people's de-sires and likes, platforms develop tools to create and steer specific needs" (Van Dijck, 2013, p. 345). Technology companies' core business involves the design of identity-based data collection and profiling systems. This means that even the most resourceful news organizations will find it difficult to deliver news through platforms such as Facebook, which can manufacture both the audience and the audience's "needs". Technology companies hold much of the data needed to fully understand how information reaches audiences. This amounts to a contemporary data blindspot, and is a factor in the erosion of trust between news organizations and the broader public. If critically important facts are unable to reach large segments of the public, then the Fourth Estate cannot effectively function as a democratic safeguard against corruption, deception, and special interests.

Trust and Data
Because the tools that the public relies on to gauge truth, fairness, and accuracy are designed around the codification of sentiment and the monetization of attention, the "fake news" battle cannot be won at the level of content alone. "Indisputable facts play only a partial role in shaping the framing words and images that flow into an audience's consciousness", notes Entman (2007). Given this scenario, objectivity, while important at the reporting level, is less valuable for establishing trust between news organizations and audiences in the "fake news" era. As more actors opt to go "direct" to their audiences using platforms like Twitter, news organizations will be forced to "follow the conversation" instead of leading the way to establish narratives that accurately inform the public through their reporting. In this regard, as Richard Tofel argues, "publishing [news] and then fact-checking is not enough" (2015).
While researchers can collect more data than ever before, much of the data that explains how "fake news" reaches and impacts its audiences is missing. Researchers must therefore focus on innovative methods to collect data: one technique that might help to address the platform data gap involves network analysis, which helps articulate the relationships between companies, political actors, governments, and the public. Network graphs (e.g., link maps) help make the invisible "visible", facilitating the system-level understanding of the "fake news" environment. For instance, network analysis can be used to display how information released by Wikileaks flows through forums like Reddit before entering "factchecking" sites like Wikipedia through article updates.
The focus on "facts" at the expense of long-term trust is one reason why I see news organizations being ineffective in preventing, and in some cases facilitating, the establishment of "alternative narratives". News reporting, as with any other type of declaration, can be ideologically, politically, and emotionally contested. The key differences in the current environment involve speed and transparency: First, people need to be exposed to the facts before the narrative can be strategically distorted through social media, distracting "leaks", troll operations, and meme warfare. Second, while technological solutions for "fake news" are a valid effort, platforms policing content through opaque technologies adds yet another disruption in the layer of trust that should be re-established directly between news organizations and their audiences.
The complex ecosystem of emerging platforms, practices, and policies marks the beginning of a new era in the study of media, politics, and information. While the mechanisms are not entirely new, when put together in the scope of global politics and civil discourse, the effects they generate create novel problems. Welcome to the era of "fake news".