scores and other sentiment indicators (Ribeiro et al., 2016).

Using GDELT data, we construct the variable _Tone News Destinationsi,m−_ 1 _,t_ , which measures the average tone of all migration-related news articles published in month _m-1_ in year _t_ in the destination countries _j_ of migrants in FMP _i_ . This is done with the formula: where _Nji_ is the number of top destination countries indicated by migrants in FMP _i_ , _xz,ji,m−_ 1 _,t_ is the tone (i.e., the sentiment) of migration-related news article _z_ published in country _j_ in month _m-1_ in year _t_ , and _Nz,ji_ is the number of migration-related news article published in destination country _j_ in that period of time.<sup>18</sup> The variable _Tone News Destinations i,m−_ 1 _,t_ has mean -2.39 and standard deviation 0.59.

We construct the same index also for different subsets of topics in migration-related news published in destination countries. To this end, we calculate the following index: where _xztopic,ji,m−_ 1 _,t_ is the sentiment of a migration-related news article discussing a specific topic published in destination country _j_ of migrants in FMP _i_ in month _m-1_ in year _t_ , while the other terms are the same as in the previous formula. In our analysis, we consider the following topics: 1) discrimination (at destination); 2) sea incidents; 3) economic conditions (at destination); 4) crime (at destination); 5) government announcements (related to migration). Finally, we create a variable measuring the tone of the migration-related news articles referring to any other topic not included in this list.<sup>19</sup> Summary statistics for these variables are shown in Table A1.

# **4.3 Other data**

**Economic activity in Libya** To compute a proxy for economic activity around the FMP, we use the intensity of night lights in the 5 km radius from the FMP’s location in the corresponding month. Night lights data are often used to measure economic activity when data to construct economic indicators are missing or badly measured, as in our case.<sup>20</sup> In our analysis, we use 18The tone of a given news article reflects the attitude towards migration of the media outlet on which it is published, e.g., its political orientation. As long as the number of outlets does not vary systematically across periods, our measure captures - given the average political orientation of all the outlets in a given country - the variation in the tone of migration-related news across time. 19 For more details on the construction of these variables, see Appendix C. The correlation between the variable _Tone News Destinations_ and a variable given by the sum of the tone of news articles by topic (i.e., _Tone News Destinations Discrimination_ + _Tone News Destinations Crime_ + _Tone News Destinations Economic conditions_ + _Tone News Destinations Sea incidents_ + _Tone News Destinations Government announcements_ + _Tone News Destinations Other_ ) is 64%. This depends on two factors: i) some news could be double counted (e.g., they refer to both discrimination and crime) and used in the construction of more than one variable; ii) the average tone of the news in a destination country is averaged with the average tone of the news in other destination countries indicated in that FMP.

> 20Data on the Libyan economy are extremely limited. Official data on economic activities were collected only until 2011. After that, statistics on the Libyan economy have been largely unreliable due to the limited capacity

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