You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
In this task, we have Spanish and Catalan tweets for automatic stance detection. The data has three labels Against, Favor, and Neutral which express the stance towards the target -independence of Catalonia. If the tweet criticizes the independence of Catalonia then it's 'Against' and if the tweets support it then it will be labeled as 'Favor' also if the tweets state information or news  rather than stating opinion then it will be characterized as 'Neutral'.

Tweet: Vull votar i votaré.  Hi ha quelcom que no em permet no fer-ho. Ara bé tinc un greu problema.  No sé a qui!!
Solution: Favor
Why? The tweet asks for the right to vote for the independence of Catalonia and it supports the movement so it will be characterized as 'Favor'.

New input: Tweet: 🔴ESTEM CONVOCATS🔴 Davant l'amenaça i els atacs de la @jusapol, T'ESPEREM A:  🏛️ Pl St Jaume 📆 Ds, 29/09 🕖 A partir d les 7h  TOT homenatge als q vam fer possible l'#1OCT, CAP als polis violents q ens van atonyinar x votar.   T'HI SUMES? #29S #OmplimSantJaume #LlibresLliures https://t.co/ZAko8oUZMD
Solution:
Favor