  Leibniz's Monadology mentions perceptional and sentimental variations of the
individual in the city. It is the interaction of people with people and events.
Film festivals are highly sentimental events of multicultural cities. Each
movie has a different sentimental effect and the interactions with the movies
have reflections that can be observed on social media. This analysis aims to
apply distant reading on Berlinale tweets collected during the festival. On
contrary to close reading, distant reading let authors to observe patterns in
large collection of data. The analysis is temporal and sentimental in
multilingual domain and strongly positive and negative time intervals are
analysed. For this purpose, we trained a deep sentiment network with
multilingual embeddings. These multilingual embeddings are aligned in latent
space. We trained the network with a multilingual dataset in three languages
English, German and Spanish. The trained algorithm has a 0.78 test score and
applied on Tweets with Berlinale hashtag during the festival. Although the
sentimental analysis does not reflect the award-winning films, we observe
weekly routine on the relationship between sentimentality, which can mislead a
close reading analysis. We have also remarks on popularity of the director or
actors.
