to goods, numbers and services is slightly over 25% more prevalent (+0.008).<sup>15</sup> Those related to politics are also more prevalent, between 16 and 100 percent (+.004 to .05). War related violence topics, especially those related to the regime, are less prevalent in return areas (-.01 to .05 points). Images also support these conclusions, with images shared in accounts from areas with only returnees between 79 and 700% more likely to be goods for sale including cars, motorcycles and other items and images from areas with neither returnees nor IDPs more likely to be tanks (+.026, 113% compared to Both) or groups of militants (+.022, 49%) as seen in Figure 6.

Adding additional granularity by considering changes pre- and post- return, we use mixed effects models to find that topics which are more represented pre-return include goods and services related topics in both the `Return Date` and seeded return model (+4% and +1.3% respectively), Figure 7. In addition, violence related topics including air strike topics are less represented both post-return and when there is less return in a given location (-1.8% `Return Date` , -3.8% seeded return with return percentage), Figures 7 and 8. Increased displacement, on the other hand, is associated with violence topics including anti-ISIS campaign and air strikes (+0.33 and +0.38 respectively), Figure 8.

In general, the clearest signal from social media is on violence-related issues, suggesting that returnees and IDPs can easily look to public groups and pages for information about ongoing conflict to inform return choices. Unsurprisingly, security considerations come first. Building on this insight, we use causal mediation analysis to reveal that information sharing on social media mediates the relationship between violent events in an area and return to that area, Figure 9.

# **5.1 Content in Return and non-Return Areas**

We first consider a model run on the `Location Mentions` dataset. This model was run with a ‘four way’ covariate including information about returnees and IDPs. The covariate equaled 1 for areas with both, 2 for areas with returnees and without IDPs, 3 for areas with IDPs and without returnees, and 4 for areas with neither. For a wholistic analysis, we considered prevalence of image clusters given the same ‘four way’ covariate. Images are from the `Researcher Coded` groups, in which no locations with only IDPs are represented. The `Location Mentions` STM model is dominated by violence related topics, motivating the use of the models discussed later in this section to attain additional insights. The most common words for each topic are in Figure 4, and the Arabic versions are available in Appendix 8.2. For the image analysis, sample clusters can be seen in Figure 5.

As shown in Figure 3 discussion around organized war violence, such as “Regime military action, Air strike”, is more represented in areas without return and without IDPs, with an increase of 0.045 between neither and both (52% more prevalent). Other violence related topics such as “Air strike warning” (0.05, 29%), “Liberation army, Regime military” (0.029, 49%), and “anti-ISIS campaign” (0.01, 33%) are also more prevalent in areas without returnees or IDPs. This result supports research indicating that individuals are unlikely to want to return to areas with ongoing violence and military campaigns, especially if they were exposed to violence prior to leaving (Ghosn et al. (2021)). Image sharing aligns with the message outcomes, with the two clearly violence related topics ‘Militants, army’ (+.026, +113% compared to Both) and ‘Construction vehicles, tanks’ (+.022, 49% compared to Both) more represented in areas without returnees or IDPs as can be seen in Figure 6.

> 15For the rest of the paper percents are calculated as the percent difference between the topic percentage value of the lower covariate and the topic percentage point value of the upper covariate. i.e. a topic with mean percent 0.05 in an area without returnees and 0.1 in an area with returnees would be noted as a 100% increase in areas with returnees.

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