## 2 Background
### Deceptive Online Content Response Techniques  
A variety of approaches have been proposed to respond to deceptive online content, once it is identified. Proposed and, in some cases, implemented technical solutions have included content filtering [15], limiting the effectiveness of botnets [57], removing content [16], limiting or preventing internet access [17], and labeling content [18].  
Worldwide, a variety of policy approaches have also been utilized. [PERSON] et al. [58] have demonstrated how numerous different approaches to regulation have been implemented by analyzing over 100 national laws. The approaches taken vary significantly.  
The European Union, for example, has utilized an approach that seeks to \"facilitate digital platforms' self-regulation to tackle misinformation and disinformation\" [59]. Indonesia, on the other hand, has laws that impose jail sentences on those convicted of \"spreading false information or news that intentionally causes public disorder\" of up to a decade [59].  
A Banglades law, despite the country's constitutional free speech protections, seeks \"to control the spread of online misinformation\" and has, according to [PERSON] et al. [60], been used to shut down publications and jail journalists.  
The People's Republic of China enacted a law, the Computer Information Network and Internet Security, Protection and Management Regulations of 1997, which prohibits \"making falsehoods or distorting the truth, spreading rumors, destroying the order of society\" on the internet. Misinformation, according to these regulations, should be removed [61].  
Ethopia prohibits certain types of \"false accusations\", while Cote d'Ivoire prohibits \"false information' that could harm the reputation of institutions\" [62]. Malawi's has a law that prohibits publishing \"false statements that may \"cause fear and alarm to the public or do disturb the public peace\"\" [62].  
In addition to technical and legal solutions that seek to prevent the creation and/or dissemination of deceptive content, other approaches have also been utilized. Labeling is one such approach. Labeling approaches, which are discussed in more detail in [18], build on a variety of initiatives for other content types and products. In the United States, MPLA movie and V-Chip television ratings [63; 64; 65] are used to label video content, while explicit lyric warning labels [66] are applied to applicable music. Other labels include anti-piracy warnings [67], food nutrition facts labels [68] and cigarette health warning labels [69].  
Labeling for online content has also been previously proposed. [PERSON] et al. [23], for example, proposed labeling content with information in multiple categories such as its level of factuality (versus opinion content), virality, emotionality, controversy, source credibility, and reading level. [PERSON] et al. [70], on the other hand, developed a system that seeks to label content based on the types of words used, classifying some as \"liberal words,\" \"conservative words,\" and \"fake news words\". Problematically, in this study [70], the system's identification of fake news, based on the applicable words, was shown to beunreliable.