# Making Sense of Language Signals for Monitoring Radicalization
## 2 From Radicalization Drivers to Radicalization Signals
The Pathway to Violence Model was developed by the United States Secret Service (USSS) through the analysis of assassins and school shooters. The model proposes six stages in the radicalization process: grievance, ideation, research and planning, preparation, breach, and attack. In addition, some works [15; 16] have applied psycholinguistic analysis of mass shooters' communications to identify recurrent topics of nihilism, ego survival, revenge fantasy, alienation, entitlement, and envy. The _Warning Behaviors Model_ was developed by the Federal Bureau of Investigation (FBI) and proposes patterns of conduct (warning behaviors) that can help law enforcement agencies to focus their investigations. The model includes eight behaviors: pathway, fixation, identification, novel aggression, energy bust leakage, last resort, and directly communicated threats. From these behaviors, the application of linguistic analysis has been successful in the identification of leakage, fixation, and identification warning behaviors [17; 18]. Leakage is the communication to a third party to harm a target, including the planning, research, or implementation of an attack [14; 17]. Fixation is any behavior that indicates that someone is increasingly preoccupied with a person or cause and is usually accompanied by deterioration in relationships or occupational performance [14]. Identification is the psychological desire to be a \"pseudocommando\" or have a \"warrior mentality.\" This includes associations with weapons and military paraphernalia and identification with previous attackers or assassins. [PERSON] et al. [17] identified linguistic markers for these warning behaviors. In particular, they proposed the use of a dictionary of violent words expanded with Wordnet [19] for terms such as _massacre_ to detect leakage. Instead, for fixation, they proposed identifying the targets of this fixation by calculating the relative frequency of entities in the text. Finally, for identification, they proposed to identify positive adjectives when mentioning ingroup and negative emotions when mentioning out-group, using software such as LIWC [9], [PERSON] et al. [18] analyzed the _alt-right_ political movement on the social network Reddit. This ideological movement is a far-right group concerned with preserving white identity. They proposed three signals for identifying fixation: increasing perseveration on the person or cause, increased negative account of object fixation, and increasingly strident opinions and angry emotional undertones. The first signal was identified using term frequency and term frequency-inverse document frequency (TF-IDF) to identify the main topics discussed in the forums (i.e., WhiteEthno, JewOrBlack, OtherRacial, and RacialSlang). As a result, they created a dictionary of terms associated with racial words. The second and third signals analyze the presence of negative emotions, anger, sadness, anxiety, the emotional tone, and texts classified as hate speech or offensive language. For this purpose, they used the LIWC [9] dictionary and the software HateSonar [20]. Finally, they proposed to characterize the warning behavior group identification with the proportion of first-person plural words, third-person plural words, and the ratio of first-person plural and third-person plural words to first-person singular words. The same categories proposed by [PERSON] et al. were analyzed by [PERSON] et al. [21] to analyze the _alternative right_ far-right political group on Twitter, commonly known as the \"alt-right\". In this case, they proposed a mesoanalysis based on social network metrics to study whether there are correlations between centrality measures and linguistic analysis. They concluded that user relevance is related to linguistic patterns of extremist discourse. Moreover, super-spreader users use more words related to far-right dictionaries. This work used the LIWC [9] dictionary and the software Vader [22] for analyzing linguistic properties and tone. [PERSON] et al.