Positron, Team 37
red-herring.vercel.app| Motivation
As of December 2020, over 125 million people in the United States have accidentally shared some formof misinformation[1]. During the 2016 US election alone, there were more than 6.6 million tweets linked toconspiracy news publishers, and over 80% of the misinformation accounts active during the election are
still active today[2]. This presents a major issue as individuals struggle to identify truth from falsehood.
According to Statista, 220 million Americans believe that fake news causes a great deal of confusion[1],and thus there exists a significant need within modern society to minimize this confusion via theimplementation of an effective, trustworthy tool.
| Product Description
Red Herring is a third-party solution aimed at tracking and combating the spread of misinformation –sometimes referred to as “red herrings” in English – with the goal of increasing trust in fact-checking onsocial media sites. To identify misinformation, Red Herring will pull from existing fact-checked sources
provided by partner social media platforms and fact-checking organizations. The company will thenapply a customized machine learning model to quickly identify posts conveying this information. Afteridentifying these posts, Red Herring will combat the spread of this misinformation by utilizing a3-pronged approach:
1. The Red Herring warning will be displayed on social media posts that have been determined byour machine learning model to contain misinformation (Figure 1).
2. After a flag has been issued, Red Herring reviews users who viewed the post prior to the flagging
and issues an “alert” to these users that contain resources to fact-checked information provided
by our partner organizations.
3. A map displaying the path of misinformation from certain sources is generated, showcasing thesource and direct contacts, enabling social media platforms to gain a better understanding of
where misinformation is coming from and how it can be dealt with.
Minor misinformation – such as wrong dates, geographical locations, or other trivial errors – will also bemarked, but users who view these posts will not be alerted. Red Herring will include an annotation thatcorrects these mistakes using its machine learning algorithm.

Figure 1. Red Herring Misinformation Detection In Action| Market Research
Many reputable third-party fact-checking organizations exist online, with the most popular US
organizations being Snopes[3] and PolitiFact[4]. While these sites are already in use, they serve users on
only their sites, therefore limiting the scope of impact. This poses an issue for social media sites, which
are hubs for creating and spreading misinformation, and are disconnected from these existing
resources. A number of social media platforms, such as Twitter and Instagram, provide native
fact-checking, but they do not provide misinformation tracing or information correction. Red Herringfinds a niche where these two services intersect. As a trustworthy fact-checker that also operates
1

https://www.statista.com/topics/3251/fake-news
https://knightfoundation.org/articles/seven-ways-misinformation-spread-during-the-2016-election
34https://www.snopes.com
https://www.politifact.com
2

on-site, users get confirmed reliable information without needing to lift a finger. Thus, the primary
motivator behind the addition of Red Herring – as opposed to, for example, each company’s own
fact-checking software – is Red Herring’s more holistic approach to misinformation identification andversatility in data reporting (i.e. generating a misinformation map). The primary disadvantage of Red
Herring is that its growth is highly dependent on its adoption by far-reaching social media platforms. A
lack of adoption results in a lack of data and squanders the efficacy of the technology, a concernaddressed through intensive marketing.
| Financial and Marketing Plans
The promotion of Red Herring is directed towards user-driven platforms such as social media sites, withthe goal of being adopted as the standard for third-party fact-checking. These figures are based on anexample scenario with three “waves” of adoption with social media platforms of conservative sizes. Dueto the unpredictable nature of additional connections, we expect the company’s growth to scale withadditional customers. For example, if a large customer implements Red Herring, the cost and humanresources needed for upkeep will increase and the company will grow accordingly.
During the developmental stage of the product, marketing resources will be diverted towards pitching
the concept to companies at industry conferences. Red Herring seeks to build trust with users throughaccurate misinformation flagging and the provision of correct information. Through a heavy emphasis
on promotion – with at least 20% of all profits being rerouted towards the marketing budget – RedHerring seeks to construct a steady and present reputation within the fact-checking industry.

Figure 2. Estimated User and Gross Data Sales Revenue Over Time

Figure 3. Red Herring 10-Year Budget

Initially, Red Herring will tackle the cost of developing and maintaining the platform through anestimated $5.75 million ($750k seed funding + $5 million series A funding), which will be distributed overthe course of the following decade. These venture capital funds will be the key source of funding during
the company’s product development and pilot phases (during the first two years following
establishment). After this, Red Herring will profit primarily by selling the third-party fact-checking
integration to social media platforms, and by providing analytic data such as misinformation spread
maps to social media companies, showing the sources of the misinformation and providing an analysis
of affected users. The community of users of Red Herring is estimated to grow to 4.1 million users inthirteen years after the end of the pilot phase (Figure 2). During this time, annual net revenue is projected
to grow at an average rate of 27% (Figure 3), with a corresponding 26% increase in the number ofemployees at the company.