Iron Curtain and Big Data are two words usually used to denote completely two different eras. Yet, the context the former offers and the rich data source the latter provides, enable the causal identification of the effect of networks on migration. Academics in countries behind the Iron Curtain were strongly isolated from the rest of the world. This context poses the question of the importance of academic networks for migration post the fall of the Berlin Wall and Iron Curtain. Using Microsoft Academic Knowledge Graph, a scholarly big data source, mapping of academics' networks is possible and information about the size and quality of their co-authorships, by location is achieved. Focusing on academics from Eastern Europe (henceforth EE) from 1980-1988 and their academic networks (1980-1988), We investigate the effect of academic network characteristics, by location, on the probability to migrate post the fall of the Berlin Wall in 1989 and up to 2003, marking the year many EE countries held referendums or signed treaties to join the EU. The unique context ensures that there was no anticipation of the fall of the Eastern Bloc and together with the data that offers unique rich information, identification is achieved. Approximately 30k academics from EE were identified, from which 3% were migrants. The results could be explained by two channels, the cost and signalling channel. The cost channel is how the network characteristic reduces or increases the cost of migration and thus