# A Framework to Understand Attitudes towards Immigration through Twitter
## 5 Results
### Dynamics and Events  
Finally, we examined changes in user engagement with the migration debate over time. We estimated the daily difference in participation rate between user profile stance; that is, proportion of users in each stance group actively engaging with Twitter content about migration (see Figure 8). A positive difference indicates greater engagement among _empathy_ users than _threat_ users, with negative values denoting greater engagement among the latter. The resulting differences are small, though notable discrepancies exist on specific dates, particularly in the second half of 2017. Peak discrepancies in engagement coincide with key migration-related events that received mass news media coverage:  
Figure 7: Proportion shift of LIWC categories in tweets grouped by _empathy_ (on the left in purple) and _threat_ (on the right in orange) attitude. * **19/04:** The Chilean Census was carried out. Tweets regarding foreign interviewers went viral (positive trend spike). * **01/07:** The National Institute of Human Rights filed a complaint against a migrant trafficking gang (positive trend spike). * **06/09:** The Minister of Home Affairs, [PERSON], faced an appeal at the National Congress after a delay in the Migration Law (negative trend spike). * **19/09:** A sign was installed in Talca (a city on central Chile) urging Haitians to join the Communist Party (negative trend spike). * **01/11:** Director of the Central Public Hospital declared that [PERSON] (Haitian woman who died after being arrested by Chilean police) had been beaten at the police station (positive trend spike). * **15/11:** Senator [PERSON] from Antofagasta (a city in northern Chile) was stabbed. He stated that \"the attacker had a foreign accent and would be a black person\" (negative trend spike). * **18/11:** Haitian immigrants attacked police in a commercial neighbourhood in downtown Santiago (negative trend spike). * **22/11:** (1) The Court declared the posthumous innocence of [PERSON]. (2) [PERSON] recognised not only the heroic act of [PERSON] (Haitian citizen who rescued a woman who fell from a building) but also a set of positive human values in migration (positive trend spike). We performed a similar analysis estimating the daily differences in the number of tweets between threat and empathy groups (see Figure 9). The results from this analysis display similar patterns of spikes as those found examining differences in user engagement. However, it highlights two key events broadcasted by the national news media: (i) [PERSON]'s announcement of a new visa for migrant children and youth through the \"Chile welcomes you\" program on 26 July (positive trend spike); and (ii) a confirmed case of an Haitian citizen with leprosy in Valdivia (a city in southern Chile) on July, 31 st (negative trend spike). We validated the differences in both measurements by comparing them with a null model, where attitudes were assigned at random (maintaining the original distribution of attitudes) in \(1\) K dataset permutations. Figures 8 and 9 display the null model timeseries. Given that the identified peaks are far from the 95% interval of each null model, the patterns described here are significant. Figure 8: Daily difference in the number of users between _empathy_ and _threat_ groups. Top: our model, and bottom: the null model. These results highlight the important role of national news media outlets in shaping the formation and expression of attitudes towards immigration in Chile. All the key events identified above were broadcasted via national television and featured on major national newspapers. As highlighted in intergroup contact and threat theories, the way in which these events are portrayed may contribute to the formation and intensified manifestation of empathetic and threatening attitudes on social media. For example, highlighted cases of physical attacks by immigrants may foment threat perceptions to public safety and hence invite expressions of negative behaviour towards immigration.