# An Algorithm for the Detection of Hidden Propaganda in Mixed-Code Text over the Internet +
## 1 Introduction  
Language is a medium of expression in human society. Communication is a form of social interaction that involves exchange or negotiation of information primarily through the use of the _language_[1]. As it is discussed in [2], languages are socio-cultural as well as individual products and, as such, they change over time, keeping up with the evolution of the social environment. IT has revolutionised the communication way [3] as evidenced by the amount of information generated and spread via social media, such as Facebook, Instagram, Twitter and YouTube. In particular, the growth of the Internet-based communication has become one of the basic necessities of the world. Thanks to such technology, many users attempt to use the Internet even for malicious purposes. The high number of users make it very easy for any kind of information to diffuse very quickly so as to influence the perception of the user itself [4]. This kind of information, mostly known as _viral messages_, is often not verified, from its authenticity point of view and it can result in outrage or hysteria. Furthermore, as discussed in [5], such methods can be used to shape public opinion, finances or even create panic in the society, that means it can be treated as an _infection of the mind_. Terrorist organisations, for example, use online networking to generate and promote propaganda based content to legitimise or instruct illegal activities to the public, as the huge amount of online registered users make the information spreadingfaster and easier [6; 7; 8]. That is why criminals exploit the Internet as an active means to perpetrate some crimes [9; 10; 11; 12]. Especially, online social media is skillfully utilised by terrorists as a tool of persuasion and behaviour change (by including political opinion, marketing and sales, humanitarian and community acts) in order to cause significant damage as well as social unrest in sensitive places by using fake news and propaganda, which might result in individuals joining terrorist networks [13; 14; 15; 16]. It is not trivial to monitor all ongoing activities even if such cyber communication takes place in the clear, without adopting any anonymous or encrypted communication techniques [17; 18]. It is difficult to recognise it, especially if it is structured in such a fashion that avoids raising the necessary security flags while reaching the intended targets. The writing style, for example, is a strong way to spread propaganda while avoiding the authorities [19]. It can represent a big obstacle from a machine perspective, to automatically detect and correctly interpret a message written in clear as a plain text. There are a few ways to enable it, such as code-mixing and mixed-code text methods. _Code-mixing_ is the term used when a person writes something using two different languages especially of two different scripts. For example, \"Aap kaise ho?\" is a text written for a Hindi person but using a Roman script. This is common parlance called a _Hinglish_ text, and likewise: _Romanji_ (Japanese in roman script), _Benglish_ (Benglish in Roman script), _Roman Urdu_ (Urdu in Roman script) and so on. Furthermore, when using code-mixing, the spelling of words tends to differ for different persons, while the variation of the phonetic usage of the Roman letters can result in varying interpretation adding to its complexity. The major challenge relies on properly monitoring these harmful messages circulating in the social network and removing or delegitimising them. This is a big concern in multilingual societies like in India where correctly identifying a potential threat is a huge hurdle. This creates a challenge for the machine to properly \"understand\" the semantics. In countries like India where multiple languages are used and social media is predominantly expressed in Roman script, a wide usage of mixed code to converse on a daily basis can be observed. However, this poses a problem to recognise the intended message in a mixed code environment.